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Janečka, Petr. "Multimodální biometrický systém kombinující duhovku a sítnici." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234910.
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This diploma thesis focuses on multibiometric systems, specifically on biometric fusion. The thesis describes eye biometrics, i.e. recognition based on retina and iris. The key part consists of design and implementation specification of a biometric system based on retina and iris recognition.
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Svoboda, Jan. "System for Recognition of 3D Hand Geometry." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-412913.
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V posledním desetiletí došlo ke zvýšení zájmu o užití 3D dat k biometrické identifikaci osob. Možná vůbec největší výzkum proběhl v oblasti 3D rozpoznávání podle obličeje, přičemž je v současné době dostupných vícero komerčních zařízení. V oblastni rozpoznávání podle 3D geometrie ruky byl v minulých letech proveden určitý výzkum jehož výsledkem však nebylo žádné komerční zařízení. Nezávisle na tomto výzkumu se v posledních letech velmi rozšířil trh s cenově dostupnými 3D sensory, což potenciálně umožňuje jejich nasazení v mnoha typech biometrických systémů. Hlavním cílem této práce je vytvořit funkční vzorek bezdotykového systému pro rozpoznávání osob podle 3D geometrie ruky, který bude používat novou levnou kameru RealSense 3D vyvíjenou v současné době firmou Intel. Jedním z problémů při použití RealSense kamery je její velmi malý form factor, který je příčinou nižší kvality výsledných snímků v porovnání s velmi drahými alternativami, které byly použity v již dříve zmíněném výzkumu 3D biometrických systémů. Práce se snaží analyzovat robustnost různých 2D a 3D příznaků a vyzkoušet několik různých přístupů k jejich fúzi. Rovněž je vyhodnocena výkonnost výsledného systému, kde je ukázáno, že navržené řešení dosahuje výsledků porovnatelných se state-of-the-art.
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Jayapal, Ranjith. "Biometric encryption system for increased security." UNF Digital Commons, 2017. http://digitalcommons.unf.edu/etd/746.
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Security is very important in present day life. In this highly-interconnected world, most of our daily activities are computer based, and the data transactions are protected by passwords. These passwords identify various entities such as bank accounts, mobile phones, etc. People might reuse the same password, or passwords related to an individual that can lead to attacks. Indeed, remembering several passwords can become a tedious task. Biometrics is a science that measures an individual’s physical characteristics in a unique way. Thus, biometrics serves as a method to replace the cumbersome use of complex passwords. Our research uses the features of biometrics to efficiently implement a biometric encryption system with a high level of security.
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Bansal, Mamta. "Face based multimodal biometric authentication system." Thesis, IIT Delhi, 2015. http://eprint.iitd.ac.in:80//handle/2074/8179.
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Semerád, Lukáš. "Generování kryptografického klíče z biometrických vlastností oka." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-236038.
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The main topic of the thesis is creation of formulas for the amount of information entropy in biometric characteristics of iris and retina. This field of science in biometrics named above is unstudied yet, so the thesis tries to initiate research in this direction. The thesis also discusses the historical context of security and identification fields according to biometric characteristics of a human being with an overlap for potential usage in biometrics of iris and retina. The Daugman’s algorithm for converting iris image into the binary code which can be used as a cryptographic key is discussed in detail. An application implementing this conversion is also a part of the thesis.
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Swabey, Matthew A. "The human auditory system as a biometric." Thesis, University of Southampton, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438725.
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Muthu, Rajesh. "Development of a secure biometric recognition system." Thesis, Northumbria University, 2016. http://nrl.northumbria.ac.uk/31618/.
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Biometric based security systems are becoming an integral part of many security agencies and organisations. These systems have a number of applications ranging from national security, law enforcement, the identification of people, particularly for building access control, the identification of suspects by the police, driver’s licences and many other spheres. However, the main challenge is to ensure the integrity of digital content under different intentional and non-intentional distortions; along with the robustness and security of the digital content. This thesis focuses on improving the security of fingerprint templates to allow accurate comparison of the fingerprint content. The current methods to generate fingerprint templates for comparison purposes mostly rely on using a single feature extraction technique such as Scale Invariant Feature Transform (SIFT) or Fingerprint Minutiae. However, the combination of two feature extraction techniques (e.g., SIFT-Minutiae) has not been studied in the literature. This research, therefore, combines the existing feature extraction techniques, SIFTHarris: Feature point detection is critical in image hashing in term of robust feature extraction, SIFT to incorporate the Harris criterion to select most robust feature points and SIFT-Wavelet: Wavelet based technique is basically used to provide more security and reliability of image, SIFT feature with efficient wavelet-based salient points to generate robust SIFT - wavelet feature that provides sufficient invariance to common image manipulations. The above said feature detector are known work well on the natural images (e.g., faces, buildings or shapes) and tests them in the new context of fingerprint images. The results in this thesis demonstrate that new approach contributes towards the improvement of fingerprint template security and accurate fingerprint comparisons. The fingerprint minutiae extraction method is combined individually with the SIFTHarris method, SIFT-Wavelet method and the SIFT method, to generate the most prominent fingerprint features. These features are post-processed into perceptual hashes using Radial Shape Context Hashing (RSCH) and Angular Shape Context Hashing (ASCH) methods. The accuracy of fingerprint comparison in each case is evaluated using the Receiver Operating Characteristic (ROC) curves. The experimental results demonstrate that for the JPEG lossy compression and geometric attacks, including rotation and translation, the fingerprint template and accuracy of fingerprint matching improved when combinations of two different Feature extraction techniques are used, in contrast to using only a single feature extraction technique. The ROC plots illustrates the SIFT-Harris-Minutiae, SIFT-Wavelet-Minutiae, SIFTMinutiae perform better than the SIFT method. The ROC plots further demonstrate that SIFT-Harris-Minutiae outperform all the other techniques. Therefore, SIFTHarris-Minutiae technique is more suitable for generating a template to compare the fingerprint content. Furthermore, this research focuses on perceptual hashing to improve the minutiae extraction of fingerprint images, even if the fingerprint image has been distorted. The extraction of hash is performed after wavelet transform and singular value decomposition (SVD). The performance evaluation of this approach includes important metrics, such as the Structural Similarity Index Measure (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). Experimentally, it has confirmed its robustness against image processing operations and geometric attacks.
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Poon, Hoi Ting. "Towards a practical and secure biometric authentication system." Thesis, University of Ottawa (Canada), 2008. http://hdl.handle.net/10393/28017.
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The idea of merging biometrics technology with cryptography brought interesting possibilities in enhancing the security and privacy of biometrics systems. Conventional systems generally require large databases, which represent a security risk and raise privacy concerns. Biometric encryption is a method devised to hide biometric features along with a cryptographic key, which could remove the need for such biometric databases. The Fuzzy Vault scheme is one of the promising candidates for biometric encryption. This thesis analyzes the scheme and attempts to provide solutions to problems impeding the system from being used in practise. We looked at the current techniques in dealing with the noise inherent in biometric templates, in particular fingerprints, and provides insight on their implication in information and biometric security. We also present two practical decoders based on the Berlekamp-Massey algorithm and the Euclidean algorithm, and provide the first implementation of a Reed-Solomon decoder for the Fuzzy Vault scheme. Our implementation results indicate that the traditional Berlekamp-Massey algorithm may not be as suitable and efficient as Gao's Reed-Solomon decoder. In our analysis, some potential vulnerabilities were also identified. In particular, the collusion attack was found to be able to seriously reduce the security of the scheme in practise and is applicable to all existing implementations. Some possible defenses against the attack such as a one-way transform of the locking set and deterministic chaff points generation were proposed.
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Han, Wei. "An integrated and distributed biometric-based user authentication architecture." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27851.
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Biometric authentication systems are used to guide the system security for many years in the computer world and make the user's identification easier and more convenient. Meanwhile, the systems encounter lots of challenges, attacks and threats, privacy protection and system management requirements, which affect the user's acceptance. Differing from the commonly used solutions, in this thesis the approach is to modify the system to meet these requirements, which results in a distributed architecture which can be composed in real time, and resolves the above challenges in one solution. A system prototype based on the proposed system architecture is designed as a sample for the reference of other system designers.
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Gibavičius, Darius. "Genetinių algoritmų taikymas biometrijoje." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20100617_141716-09318.
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Baigiamajame magistro darbe nagrinėjamas genetinių algoritmų taikymas biometrijoje. Išnagrinėta plačiausiai naudojama biometrinė informacija, aprašytos labiausiai paplitusios biometrinės sistemos, genetiniai algoritmai bei jų pritaikymas biometrinių sistemų optimizavimui. Baigiamajame darbe pasiūlytas naujas rankos atpažinimo metodas. Šiam metodui pritaikyti genetiniai algoritmai. Darbą sudaro 7 dalys: įvadas, biometrija, genetiniai algoritmai, genetinių algoritmų taikymas biometrinėse sistemose, genetinių algoritmų taikymas rankos atpažinimui, išvados ir literatūra. Darbo apimtis – 51 p. teksto be priedų, 30 pav., 4 lent., 32 bibliografiniai šaltiniai.<br>In the graduation thesis to receive the master‘s degree the application of genetic algorithms in biometrics is analysed. The most widely used biometric information have been examined, the most common biometric systems, genetic algorithms and their customization in biometric systems optimization have been described. A new method is proposed for hand recognition. Genetic algorithms have been customized for this method. Structure: introduction, biometry, genetic algorithms, application of genetic algorithms in biometric systems, application of genetic algorithms for hand recognition, the conclusions and bibliography. Thesis consist of: 51 p. text without appendixes, 30 pictures, 4 tables, 32 bibliographical entries.
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Kuan, Hung-i. "Evaluation of a biometric keystroke typing dynamics computer security system." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/26530.
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Approved for public release; distribution is unlimited.<br>This study evaluates an inexpensive personal computer access control system that relies on biometric keystroke typing dynamics technology, BioPassword Model 2100 (BioPassword). Enrollment time, verification time, false rejection error rate, false acceptance error rate, and user acceptance were evaluated for this system. The results show that BioPassword provides multilayer security through the inclusion of privilege control, audit functions, passwords, and verification of a personal behavioral characteristic, the rate and variation of typing a given password string. Enrollment and verification times were considered satisfactorily fast. Overall false rejection error rate was 22.5%, while false acceptance error rate was 3.4%. The false rejection error rate for acceptance as a function of trial number from one trial to five trials were 4. 4%, 1.4%, O.7%, O.4%, andO.3% respectively. These values were achieved under relatively uncontrolled conditions and should be improved on by using recommendations that are included. Users generally reported satisfaction with the system, which should be acceptable as part of an office automation system when used in conjunction with other standard security measures. BioPassword Model 21 00, Biometric technology, Keystroke Typing Dynamics, False Rejection Error Rate, False Acceptance Error Rate, Enrollment Time, Verification Time
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Assaad, Firas Souhail. "Biometric Multi-modal User Authentication System based on Ensemble Classifier." University of Toledo / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1418074931.
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Mai, Guangcan. "Biometric system security and privacy: data reconstruction and template protection." HKBU Institutional Repository, 2018. https://repository.hkbu.edu.hk/etd_oa/544.
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Biometric systems are being increasingly used, from daily entertainment to critical applications such as security access and identity management. It is known that biometric systems should meet the stringent requirement of low error rate. In addition, for critical applications, the security and privacy issues of biometric systems are required to be concerned. Otherwise, severe consequence such as the unauthorized access (security) or the exposure of identity-related information (privacy) can be caused. Therefore, it is imperative to study the vulnerability to potential attacks and identify the corresponding risks. Furthermore, the countermeasures should also be devised and patched on the systems. In this thesis, we study the security and privacy issues in biometric systems. We first make an attempt to reconstruct raw biometric data from biometric templates and demonstrate the security and privacy issues caused by the data reconstruction. Then, we make two attempts to protect biometric templates from being reconstructed and improve the state-of-the-art biometric template protection techniques.
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Mohamed, Abdul Cader Akmal Jahan. "Finger biometric system using bispectral invariants and information fusion techniques." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/134464/1/Akmal%20Jahan_Mohamed%20Abdul%20Cader_Thesis.pdf.
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Contactless hand biometric systems are better accepted than contact prints as they are hygienic and accelerate data acquisition. This research is one of the few investigating contactless biometrics of the full hand by proposing a novel algorithm based on ridge orientation information along lines connecting key points, higher order spectral features, and fusion. It was investigated with contactless finger images acquired from 81 users, and found to be robust to hand orientation and image size, and provide acceptable performance using two fingers with fusion. The algorithm has potential to use in high throughput applications where contact sensing may be slow.
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Hasegawa, Robert Shigehisa. "Using synthetic images to improve iris biometric performance." Scholarly Commons, 2012. https://scholarlycommons.pacific.edu/uop_etds/827.
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Clarke, Dalton H., and W. Tracy Young. "Reengineering of the Defense Biometric Identification System (DBIDS) equipment tracking database." Thesis, Monterey, California. Naval Postgraduate School, 2009. http://hdl.handle.net/10945/4607.
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Approved for public release, distribution unlimited<br>The Defense Manpower Data Center (DMDC) manages the Defense Biometric Identification System (DBIDS). DBIDS captures personal and biometric information to manage DoD-wide access, control, and personnel accountability. DBIDS equipment is installed globally, and managed by a central office on the Monterey peninsula. Program managers track data about the numbers and type of equipment installed at each site. Program managers were tracking DBIDS data using a single Microsoft Excel workbook comprised of several, interlinking worksheets (DBIDS Master Plan Spreadsheet). Data updates were error-prone and difficult, requiring close coordination to keep the number of "current" versions of the spreadsheet to a minimum. This thesis initially focused on reviewing the business rules and processes surrounding DBIDS document, and then transitioned into designing, developing, and implementing of a relational database solution to improve problem areas identified during the initial review. After implementation of the database, this thesis explored the effects of making such a change within an organization. This was attempted by identifying and measuring changes in performance and accuracy of the system; by measuring pre- and post-user satisfaction through the qualitative methods of questionnaires and interviews; and finally using this analysis to improve the project through maintenance and growth iterations.
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Young, W. Tracy Clarke Dalton H. "Reengineering of the Defense Biometric Identification System (DBIDS) equipment tracking database." Monterey, California : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Sep/09Sep%5FYoung.pdf.
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Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, September 2009. Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, March 2009.<br>Thesis Advisor(s): Pfeiffer, Karl D. "September 2009." Description based on title screen as viewed on 6 November, 2009. Author(s) subject terms: Database, Database Development Life Cycle, Rapid Prototyping, Business Process Management Software, Business Process Improvement, Business Process Redesign. Includes bibliographical references (p. 63-65). Also available in print.
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Arteaga, Falconi Juan Sebastian. "Towards an Accurate ECG Biometric Authentication System with Low Acquisition Time." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40129.
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Biometrics is the study of physical or behavioral traits that establishes the identity of a person. Forensics, physical security and cyber security are some of the main fields that use biometrics. Unlike traditional authentication systems—such as password based—biometrics cannot be lost, forgotten or shared. This is possible because biometrics establishes the identity of a person based on a physiological/behavioural characteristic rather than what the person possess or remembers. Biometrics has two modes of operation: identification and authentication. Identification finds the identity of a person among a group of persons. Authentication determines if the claimed identity of a person is truthful.
Biometric person authentication is an alternative to passwords or graphical patterns. It prevents shoulder surfing attacks, i.e., people watching from a short distance. Nevertheless, biometric traits of conventional authentication techniques like fingerprints, face—and to some extend iris—are easy to capture and duplicate. This denotes a security risk for modern and future applications such as digital twins, where an attacker can copy and duplicate a biometric trait in order to spoof a biometric system. Researchers have proposed ECG as biometric authentication to solve this problem. ECG authentication conceals the biometric traits and reduces the risk of an attack by duplication of the biometric trait. However, current ECG authentication solutions require 10 or more seconds of an ECG signal in order to have accurate results. The accuracy is directly proportional to the ECG signal time-length for authentication. This is inconvenient to implement ECG authentication in an end-user product because a user cannot wait 10 or more seconds to gain access in a secure manner to their device.
This thesis addresses the problem of spoofing by proposing an accurate and secure ECG biometric authentication system with relatively short ECG signal length for authentication. The system consists of an ECG acquisition from lead I (two electrodes), signal processing approaches for filtration and R-peak detection, a feature extractor and an authentication process. To evaluate this system, we developed a method to calculate the Equal Error Rate—EER—with non-normal distributed data.
In the authentication process, we propose an approach based on Support Vector Machine—SVM—and achieve 4.5% EER with 4 seconds of ECG signal length for authentication. This approach opens the door for a deeper understanding of the signal and hence we enhanced it by applying a hybrid approach of Convolutional Neural Networks—CNN—combined with SVM. The purpose of this hybrid approach is to improve accuracy by automatically detect and extract features with Deep Learning—in this case CNN—and then take the output into a one-class SVM classifier—Authentication; which proved to outperform accuracy for one-class ECG classification. This hybrid approach reduces the EER to 2.84% with 4 seconds of ECG signal length for authentication.
Furthermore, we investigated the combination of two different biometrics techniques and we improved the accuracy to 0.46% EER, while maintaining a short ECG signal length for authentication of 4 seconds. We fuse Fingerprint with ECG at the decision level. Decision level fusion requires information that is available from any biometric technique. Fusion at different levels—such as feature level fusion—requires information about features that are incompatible or hidden. Fingerprint minutiae are composed of information that differs from ECG peaks and valleys. Therefore fusion at the feature level is not possible unless the fusion algorithm provides a compatible conversion scheme. Proprietary biometric hardware does not provide information about the features or the algorithms; therefore, features are hidden and not accessible for feature level fusion; however, the result is always available for a decision level fusion.
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Bashir, Muzaffar [Verfasser], and Hans Robert [Akademischer Betreuer] Kalbitzer. "A novel multisensoric system recording and analyzing human biometric features for biometric and biomedical applications / Muzaffar Bashir. Betreuer: Hans Robert Kalbitzer." Regensburg : Universitätsbibliothek Regensburg, 2011. http://d-nb.info/102331214X/34.
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Lam, Lawrence G. "Digital Health-Data platforms : biometric data aggregation and their potential impact to centralize Digital Health-Data." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/106235.
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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, Engineering and Management Program, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (page 81).<br>Digital Health-Data is being collected at unprecedented rates today as biometric micro sensors continue to diffuse into our lives in the form of smart devices, wearables, and even clothing. From this data, we hope to learn more about preventative health so that we can spend less money on the doctor. To help users aggregate this perpetual growth of biometric "big" data, Apple HealthKit, Google Fit, and Samsung SAMI were each created with the hope of becoming the dominant design platform for Digital Health-Data. The research for this paper consists of citings from technology strategy literature and relevant journalism articles regarding recent and past developments that pertain to the wearables market and the digitization movement of electronic health records (EHR) and protected health information (PHI) along with their rules and regulations. The culmination of these citations will contribute to my hypothesis where the analysis will attempt to support my recommendations for Apple, Google, and Samsung. The ending chapters will encompass discussions around network effects and costs associated with multi-homing user data across multiple platforms and finally ending with my conclusion based on my hypothesis.<br>by Lawrence G. Lam.<br>S.M. in Engineering and Management
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Feng, Yicheng. "Template protecting algorithms for face recognition system." HKBU Institutional Repository, 2007. http://repository.hkbu.edu.hk/etd_ra/832.
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Lodrová, Dana. "Rozpoznávání živosti otisků prstů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2007. http://www.nusl.cz/ntk/nusl-236887.
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This document deals with presentation of nowadays software and hardware methods used for fingerprint recognition with focus on liveness testing and thereafter it deals with description of my solution. In order to describe results obtained from study of technical literature, we discuss important terminology of biometric systems at first and further main principles of fingerprint sensors used in practice are shown. From overviewed methods of liveness detection we underline one method based on perspiration (researched by BioSAL laboratory) and one spectroscopic method researched by Lumidigm Corporation. The study of liveness testing methods inspired me to creation of new type fingerprint sensor which has built-in livennes testing method based on two characteristic properties of living human tisue. In order to test this sensor, we discuss nowadays sensor deception method. It follows from their analysis, that newly designed sensor should be theoretically resistant to each of them.
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Abraham, Arya. "It is I: An Authentication System for a Reconfigurable Radio." Thesis, Virginia Tech, 2002. http://hdl.handle.net/10919/34353.
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The security of a radio system hinges on its ability to effectively authenticate a user. This work proposes a two-factor authentication scheme using a token and a biometric. The users' access rights are determined during authentication and the users are served only those channels of data that they are privileged to receive. The strengths and the weaknesses of the implementation in reconfigurable hardware are identified. The capabilities of the scheme are put into perspective by comparing it to a high-end authentication system and by evaluating the use of standardized APIs and low-end authentication devices. Modifications to the system are suggested to improve the level of security the scheme provides. Finally, a baseline study is carried out to measure the data processing performance of a radio developed in reconfigurable hardware, which uses the proposed authentication scheme.<br>Master of Science
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Louw, Lloyd A. B. "Automated face detection and recognition for a login system." Thesis, Link to the online version, 2007. http://hdl.handle.net/10019/438.
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Pokorný, Karel. "Jádro multimodálního biometrického systému." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236471.
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The aim of this thesis is a design and realization of the core of multimodal biometric system. First part of the thesis sumarizes contemporary knowledge about biometric systems and about combination of their outputs. Second part introduces concept and implementation of multimodal biometric system, which uses weighted score combination and user-specific weights.
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McMillan, Stephen. "Design and analysis of a biometric access control system using an electronic olfactory device to identify human odour characteristics." Thesis, University of Greenwich, 2000. http://gala.gre.ac.uk/13136/.
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The use of an electronic olfactory device, termed an electronic 'nose', was investigated for the detection of unique human odour characteristics. The detection of these unique odours was applied to the field of biometrics for access control, where a human's unique characteristics were used to authenticate a user of an access control system. An electronic odour sensing device was designed and constructed using an array of conducting polymer gas sensors in order to facilitate the regular screening of a group of human subjects over a period of six weeks. A static sampling method was used to measure odour levels from human hands, which were found to contain a reliable source of human odour. Human odour levels were low so dynamic sampling proved to be unsuitable for this application due to the dilution of the odour mixture. Feature analysis results revealed that the features of adsorption and desorption gradient contained discriminatory information in addition to the commonly used maximum divergence. Pattern recognition revealed that neural network architectures produced superior results when compared to statistical methods as a result of their ability to model the non-linearities in the data set. The highest recognition rate was 73% which was produced using a Multi-Layer Perceptron (MLP) neural network compared to 63% obtained using the best statistical method of Parzen windows. The majority of the recognition error was caused by a minority of the humans. Analysis of sensor data revealed that only 30% of the sensor array were contributing discriminatory information so it was deduced that performance would undoubtedly improve if a full array of effective sensors were available. Exploratory data analysis revealed that human odour changed from day to day and often an increasing divergence with time was observed. A time-adaptive method was devised which increased the recognition to 89%, but was still too low for use as a biometric recognition device. However, use as a verification device demonstrated acceptable levels of performance but resulted in high levels of user frustration caused by a high proportion of users being falsely rejected. This work demonstrated that an olfactory based biometric access control system could be a realistic proposition but requires further work, especially in the areas of sensor development and unique human odour research, before an operational system could be produced.
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Костомаха, Марія Володимирівна, та Mariia Kostomakha. "Комп’ютерна система біометричної аутентифікації особи за відбитком пальця". Bachelor's thesis, Тернопільський національний технічний університет імені Івана Пулюя, 2021. http://elartu.tntu.edu.ua/handle/lib/35567.
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У кваліфікаційній роботі спроектовано комп’ютерну систему біометричної аутентифікації особи за відбитком пальців, що відповідає вимогам технічного завдання.
Основними апаратними пристроями спроектованої системи є: сканер відбитків пальців на основі ZFM-20; пристрій керування процесом зчитування та аутентифікації особи Raspberry PI Model B; компонента виводу інформаційних повідомлень для взаємодії з користувачем LCD 2*16.
Взаємодію між сканером відбитків пальців і Raspberry PI забезпечено шляхом використання USB Serial адаптера. Логіку роботи програмного забезпечення реалізовано засобами мови програмування Python, що підтримується обраним однокристальним міні-комп’ютером.<br>In the qualification work, a computer system of biometric authentication of a person by fingerprint is designed, which meets the requirements of the technical task. The goal of the work was achieved through the use of sound hardware and developed software.
The main hardware devices of the designed system are: fingerprint scanner based on ZFM-20; Raspberry PI Model B reading and authentication process control device; component for outputting information messages for interaction with the user LCD 2 * 16.
The interaction between the fingerprint scanner and the Raspberry PI is provided by using a USB Serial adapter. The success of the authentication is additionally signaled by the LED. The logic of the software is implemented using Python programming language supported by the selected single-chip mini-computer.<br>ПЕРЕЛІК ОСНОВНИХ УМОВНИХ ПОЗНАЧЕНЬ, СИМВОЛІВ І СКОРОЧЕНЬ 8
ВСТУП 9
1 АНАЛІЗ ВИМОГ ТЕХНІЧНОГО ЗАВДАННЯ ТА МЕТОДІВ БІОМЕТРИЧНОЇ АУТЕНТИФІКАЦІЇ ОСОБИ 10
1.1 Аналіз вимог технічного завдання на проектування комп’ютерної системи біометричної аутентифікації особи за відбитком пальця 10
1.2 Методи і засоби аутентифікації особи 16
2 РОЗРОБКА ПРОЕКТУ КОМП’ЮТЕРНОЇ СИСТЕМИ БІОМЕТРИЧНОЇ АУТЕНТИФІКАЦІЇ ОСОБИ ЗА ВІДБИТКОМ ПАЛЬЦІВ 22
2.1 Архітектура комп’ютерної системи біометричної аутентифікації 22
2.2 Обґрунтування вибору та аналіз технічних характеристики Raspberry PI 24
2.3 Аналіз технічних характеристик сканера відбитків пальців 28
2.4 Особливості застосування LCD-дисплея 32
2.5 Перетворювач USB – UART 35
2.6 Побудова схеми комп’ютерної системи біометричної аутентифікації особи за відбитком пальця 36
3 ПРОГРАМНЕ ЗАБЕЗПЕЧЕННЯ КОМП’ЮТЕРНОЇ СИСТЕМИ БІОМЕТРИЧНОЇ АУТЕНТИФІКАЦІЇ ОСОБИ ЗА ВІДБИТКОМ ПАЛЬЦІВ 41
3.1 Реалізація логіки роботи програмного забезпечення комп’ютерної системи біометричної аутентифікації 41
3.2 Тестування комп’ютерної системи аутентифікації особи 53
РОДІЛ 4 БЕЗПЕКА ЖИТТЄДІЯЛЬНОСТІ, ОСНОВИ ОХОРОНИ ПРАЦІ 56
4.1 Вплив виробничого середовища на працездатність та здоров'я користувачів
комп'ютерів 56
4.2 Захист населення у надзвичайних ситуаціях від впливу радіації 59
ВИСНОВКИ 56
СПИСОК ВИКОРИСТАНИХ ДЖЕРЕЛ 57
Додаток A. Технічне завдання
Додаток Б. Програмне забезпечення комп’ютерної системи біометричної аутентифікації особи за відбитком пальця
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Li, Jiawei. "Person re-identification with limited labeled training data." HKBU Institutional Repository, 2018. https://repository.hkbu.edu.hk/etd_oa/541.
Full textAbstract:
With the growing installation of surveillance video cameras in both private and public areas, it is an immediate requirement to develop intelligent video analysis system for the large-scale camera network. As a prerequisite step of person tracking and person retrieval in intelligent video analysis, person re-identification, which targets in matching person images across camera views is an important topic in computer vision community and has been received increasing attention in the recent years. In the supervised learning methods, the person re-identification task is formulated as a classification problem to extract matched person images/videos (positives) from unmatched person images/videos (negatives). Although the state-of-the-art supervised classification models could achieve encouraging re-identification performance, the assumption that label information is available for all the cameras, is impractical in large-scale camera network. That is because collecting the label information of every training subject from every camera in the large-scale network can be extremely time-consuming and expensive. While the unsupervised learning methods are flexible, their performance is typically weaker than the supervised ones. Though sufficient labels of the training subjects are not available from all the camera views, it is still reasonable to collect sufficient labels from a pair of camera views in the camera network or a few labeled data from each camera pair. Along this direction, we address two scenarios of person re-identification in large-scale camera network in this thesis, i.e. unsupervised domain adaptation and semi-supervised learning and proposed three methods to learn discriminative model using all available label information and domain knowledge in person re-identification. In the unsupervised domain adaptation scenario, we consider data with sufficient labels as the source domain, while data from the camera pair missing label information as the target domain. A novel domain adaptive approach is proposed to estimate the target label information and incorporate the labeled data from source domain with the estimated target label information for discriminative learning. Since the discriminative constraint of Support Vector Machines (SVM) can be relaxed into a necessary condition, which only relies on the mean of positive pairs (positive mean), a suboptimal classification model learning without target positive data can be those using target positive mean. A reliable positive mean estimation is given by using both the labeled data from the source domain and potential positive data selected from the unlabeled data in the target domain. An Adaptive Ranking Support Vector Machines (AdaRSVM) method is also proposed to improve the discriminability of the suboptimal mean based SVM model using source labeled data. Experimental results demonstrate the effectiveness of the proposed method. Different from the AdaRSVM method that using source labeled data, we can also improve the above mean based method by adapting it onto target unlabeled data. In more general situation, we improve a pre-learned classifier by adapting it onto target unlabeled data, where the pre-learned classifier can be domain adaptive or learned from only source labeled data. Since it is difficult to estimate positives from the imbalanced target unlabeled data, we propose to alternatively estimate positive neighbors which refer to data close to any true target positive. An optimization problem for positive neighbor estimation from unlabeled data is derived and solved by aligning the cross-person score distributions together with optimizing for multiple graphs based label propagation. To utilize the positive neighbors to learn discriminative classification model, a reliable multiple region metric learning method is proposed to learn a target adaptive metric using regularized affine hulls of positive neighbors as positive regions. Experimental results demonstrate the effectiveness of the proposed method. In the semi-supervised learning scenario, we propose a discriminative feature learning using all available information from the surveillance videos. To enrich the labeled data from target camera pair, image sequences (videos) of the tagged persons are collected from the surveillance videos by human tracking. To extract the discriminative and adaptable video feature representation, we propose to model the intra-view variations by a video variation dictionary and a video level adaptable feature by multiple sources domain adaptation and an adaptability-discriminability fusion. First, a novel video variation dictionary learning is proposed to model the large intra-view variations and solved as a constrained sparse dictionary learning problem. Second, a frame level adaptable feature is generated by multiple sources domain adaptation using the variation modeling. By mining the discriminative information of the frames from the reconstruction error of the variation dictionary, an adaptability-discriminability (AD) fusion is proposed to generate the video level adaptable feature. Experimental results demonstrate the effectiveness of the proposed method.
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Nandakumar, Karthik. "Multibiometric systems fusion strategies and template security /." Diss., Connect to online resource - MSU authorized users, 2008.
Find full textAbstract:
Thesis (Ph. D.)--Michigan State University. Dept. of Computer Science and Engineering, 2008.<br>Title from PDF t.p. (viewed on Mar. 30, 2009) Includes bibliographical references (p. 210-228). Also issued in print.
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Jomaa, Diala. "Fingerprint Segmentation." Thesis, Högskolan Dalarna, Datateknik, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:du-4264.
Full textAbstract:
In this thesis, a new algorithm has been proposed to segment the foreground of the fingerprint from the image under consideration. The algorithm uses three features, mean, variance and coherence. Based on these features, a rule system is built to help the algorithm to efficiently segment the image. In addition, the proposed algorithm combine split and merge with modified Otsu. Both enhancements techniques such as Gaussian filter and histogram equalization are applied to enhance and improve the quality of the image. Finally, a post processing technique is implemented to counter the undesirable effect in the segmented image. Fingerprint recognition system is one of the oldest recognition systems in biometrics techniques. Everyone have a unique and unchangeable fingerprint. Based on this uniqueness and distinctness, fingerprint identification has been used in many applications for a long period. A fingerprint image is a pattern which consists of two regions, foreground and background. The foreground contains all important information needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false minutiae in the system. To avoid the extraction of false minutiae, there are many steps which should be followed such as preprocessing and enhancement. One of these steps is the transformation of the fingerprint image from gray-scale image to black and white image. This transformation is called segmentation or binarization. The aim for fingerprint segmentation is to separate the foreground from the background. Due to the nature of fingerprint image, the segmentation becomes an important and challenging task. The proposed algorithm is applied on FVC2000 database. Manual examinations from human experts show that the proposed algorithm provides an efficient segmentation results. These improved results are demonstrating in diverse experiments.
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Pereira, Tiago de Freitas 1985. "A comparative study of countermeasures to detect spoofing attacks in face authentication systems = Um estudo comparativo de contramedidas para detectar ataques de spoofing em sistemas de autenticação de faces." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/261478.
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Orientador: José Mario De Martino<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-23T20:06:41Z (GMT). No. of bitstreams: 1
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Previous issue date: 2013<br>Resumo: O Resumo poderá ser visualizado no texto completo da tese digital<br>Abstract: The complete Abstract is available with the full electronic document.<br>Mestrado<br>Engenharia de Computação<br>Mestre em Engenharia Elétrica
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Váňa, Tomáš. "Biometrické rozpoznání živosti prstu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221380.
Full textAbstract:
This master‘s thesis deals with biometric fingerprint liveness detection. The theoretical part of the work describes fingerprint recognition biometric systems, fingerprint liveness detection issues and methods for fingerprint liveness detection. The practical part of the work describes proposed set of discriminant features and preprocessing of fingerprint image. Proposed approach using neural network to detect a liveness. The algorithm is tested on LivDet database comprising real and fake images acquired with tree sensors. Classification performance approximately 93% was obtained.
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Öberg, Fredrik. "Investigation on how presentation attack detection can be used to increase security for face recognition as biometric identification : Improvements on traditional locking system." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42294.
Full textAbstract:
Biometric identification has already been applied to society today, as today’s mobile phones use fingerprints and other methods like iris and the face itself. With growth for technologies like computer vision, the Internet of Things, Artificial Intelligence, The use of face recognition as a biometric identification on ordinary doors has become increasingly common. This thesis studies is looking into the possibility of replacing regular door locks with face recognition or supplement the locks to increase security by using a pre-trained state-of-the-art face recognition method based on a convolution neural network. A subsequent investigation concluded that a networks based face recognition are is highly vulnerable to attacks in the form of presentation attacks. This study investigates protection mechanisms against these forms of attack by developing a presentation attack detection and analyzing its performance. The obtained results from the proof of concept showed that local binary patterns histograms as a presentation attack detection could help the state of art face recognition to avoid attacks up to 88\% of the attacks the convolution neural network approved without the presentation attack detection. However, to replace traditional locks, more work must be done to detect more attacks in form of both higher percentage of attacks blocked by the system and the types of attack that can be done. Nevertheless, as a supplement face recognition represents a promising technology to supplement traditional door locks, enchaining their security by complementing the authorization with biometric authentication. So the main contributions is that by using simple older methods LBPH can help modern state of the art face regognition to detect presentation attacks according to the results of the tests. This study also worked to adapt this PAD to be suitable for low end edge devices to be able to adapt in an environment where modern solutions are used, which LBPH have.
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Navrátil, Petr. "Podpora výuky biometrických přístupových systémů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217304.
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This thesis describes general function of biometric access systems and summarizes problems of their practical use. It also shows security risks of these systems. It defines basic terms, which are used in this area, describes kinds of errors and their representation. One part of this thesis deals with biometric method of fingerprints recognition. It explains fingerprints’ atomic basics, basic principles and processing of digital fingerprint image. Next part describes concrete biometric access system V-Station by Bioscrypt Inc. Besides basic description it focuses on technology of biometric sensor and algorithm, essential parts of biometric system. The thesis continues with security analysis of this concrete system. In this part I target on weak points of the system and I design possible attack on the system. In the last part of my thesis I designed laboratory exercise, which is supposed to be realized by student. It is composed it by several tasks to let students understand working with the system and attached software. At the same time, they have opportunity to think about system by themselves a make their own opinion about possibilities of the system. There are many pictures in this thesis to make term clear and to better understanding of problems of biometric security systems.
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Laurinavičiūtė, Viktorija. "Nekilnojamojo turto įmonės darbo efektyvumo didinimas naudojant biometrinę pelytę." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2009~D_20090615_104023-15073.
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Baigiamajame magistro darbe nagrinėjamas nekilnojamojo turto įmonių darbuotojų darbo efektyvumas ir jo didinimo galimybės panaudojant naujausias technologijas – biometrinę kompiuterio pelytę bei VGTU studentų ir dėstytojų sukurtą internetinę ekspertinę sistemą, duodančią patarimus darbuotojų našumui didinti. Darbe apibendrintai aprašomas Lietuvos ūkio darbo našumas, jo pasikeitimai per pastaruosius metus, bei veiksniai, turintys didžiausią įtaką darbo našumui. Taip pat darbe aprašomos biometrinės technologijos, apžvelgiamas jų panaudojimas nekilnojamojo turto sektoriuje ir galimybė jas pritaikyti darbo efektyvumui didinti. Atlikus stebėjimus biometrine kompiuterio pelyte ir nustačius didžiausią įtaką darbuotojų našumui darančius veiksnius, remiantis A. Maslowo poreikių teorija buvo sukurta ekspertinė darbo našumo didinimo sistema. Išanalizavus darbo su biometrine pelyte ir sukurta ekspertine sistema rezultatus, darbo gale pateikiamos darbo išvados ir pasiūlymai.<br>The labour productivity problem and possibility to improve labour productivity by using biometric technologies and web-based expert system, developed by students and academics of VGTU is analyzed in this thesis. Summarized description of the labour productivity in general, its progress during few past years in Lithuania and factors that make the biggest influence on the level of labour productivity are described. Also the work contains overview of the biometric systems, usage of them in real estate and the possibility to increase labour productivity. After making observations during work with biometric mouse and identifying factors that affect productivity the most, the expert system, based on the A.Maslows hierarchy of needs was developed. Conclusion and suggestions were made after performing the analysis of the results of working with the biometric mouse and web-based expert system.
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Fouad, Marwa. "Towards Template Security for Iris-based Biometric Systems." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/22736.
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Personal identity refers to a set of attributes (e.g., name, social insurance number, etc.) that are associated with a person. Identity management is the process of creating, maintaining and destroying identities of individuals in a population. Biometric technologies are technologies developed to use statistical analysis of an individual’s biological or behavioral traits to determine his identity. Biometrics based authentication systems offer a reliable solution for identity management, because of their uniqueness, relative stability over time and security (among other reasons). Public acceptance of biometric systems will depend on their ability to ensure robustness, accuracy and security. Although robustness and accuracy of such systems are rapidly improving, there still remain some issues of security and balancing it with privacy. While the uniqueness of biometric traits offers a convenient and reliable means of identification, it also poses the risk of unauthorized cross-referencing among databases using the same biometric trait. There is also a high risk in case of a biometric database being compromised, since it’s not possible to revoke the biometric trait and re-issue a new one as is the case with passwords and smart keys. This unique attribute of biometric based authentication system poses a challenge that might slow down public acceptance and the use of biometrics for authentication purposes in large scale applications.
In this research we investigate the vulnerabilities of biometric systems focusing on template security in iris-based biometric recognition systems. The iris has been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. The most widely accepted iris recognition systems are based on Daugman’s model that creates a binary iris template. In this research we develop different systems using watermarking, bio-cryptography as well as feature transformation to achieve revocability and security of binary templates in iris based biometric authentication systems, while maintaining the performance that enables widespread application of these systems. All algorithms developed in this research are applicable on already existing biometric authentication systems and do not require redesign of these existing, well established iris-based authentication systems that use binary templates.
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Mehdi, Ali. "Developing a Computer System for the Generation of Unique Wrinkle Maps for Human Faces. Generating 2D Wrinkle Maps using Various Image Processing Techniques and the Design of 3D Facial Ageing System using 3D Modelling Tools." Thesis, University of Bradford, 2011. http://hdl.handle.net/10454/5144.
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Facial Ageing (FA) is a very fundamental issue, as ageing in general, is part of our daily life process. FA is used in security, finding missing children and other applications. It is also a form of Facial Recognition (FR) that helps identifying suspects. FA affects several parts of the human face under the influence of different biological and environmental factors. One of the major facial feature changes that occur as a result of ageing is the appearance and development of wrinkles. Facial wrinkles are skin folds; their shapes and numbers differ from one person to another, therefore, an advantage can be taken over these characteristics if a system is implemented to extract the facial wrinkles in a form of maps. This thesis is presenting a new technique for three-dimensional facial wrinkle pattern information that can also be utilised for biometric applications, which will back up the system for further increase of security. The procedural approaches adopted for investigating this new technique are the extraction of two-dimensional wrinkle maps of frontal human faces for digital images and the design of three-dimensional wrinkle pattern formation system that utilises the generated wrinkle maps. The first approach is carried out using image processing tools so that for any given individual, two wrinkle maps are produced; the first map is in a binary form that shows the positions of the wrinkles on the face while the other map is a coloured version that indicates the different intensities of the wrinkles. The second approach of the 3D system development involves the alignment of the binary wrinkle maps on the corresponding 3D face models, followed by the projection of 3D curves in order to acquire 3D representations of the wrinkles. With the aid of the coloured wrinkle maps as well as some ageing parameters, simulations and predictions for the 3D wrinkles are performed.
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Klimešová, Lenka. "Identifikace osob pomocí biometrie sítnice." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2018. http://www.nusl.cz/ntk/nusl-378031.
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This paper deals with identification of persons using retinal biometry. The retinal vasculature is invariant and unique to everyone, which determines it for biometric purposes. The first part of the work includes information about biometrics, biometric systems and reliability measures. The next part describes the principle of using experimental video ophthalmoscope, which was used for retinal vascular imaging and includes the literature research of use of retinal images for biometrics, feature extraction methods and similarity measures. Finally, two algorithms to use the input data are proposed and realized in programming environment MATLAB®. The methods are tested and evaluated on a data set from experimental video ophthalmoscope and on publicly available STRaDe and DRIVE databases.
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Faria, Bruno Guedes. "Implementação e avaliação do ABID (Aplicativo Biométrico de Impressão Digital) utilizando o método fuzzy vault e ferramentas opensource." Universidade Presbiteriana Mackenzie, 2014. http://tede.mackenzie.br/jspui/handle/tede/1442.
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Previous issue date: 2014-06-10<br>Universidade Presbiteriana Mackenzie<br>Biometric Systems has increasingly been growing in the past years, mainly those based on fingerprints. In terms of security, they need the same care which is given to traditional systems that uses cards and passwords. The Fuzzy Vault methods comes
in this scenario to provide security to biometric systems, specifically, protecting the stored biometric template. This
research will present the Fuzzy Vault scheme development and
how it can be used to hide a 128 bits secret. The scheme will be
used into the context of a biometric application based on fingerprints. Evaluation of security and performance of the application will be shown, as well as the experimental
results, common to biometric systems FRR (False Rejection Rate), GAR (Genuine Accept Rate), FAR (False Accept Rate).<br>A utilização de sistemas biométricos tem apresentado um cenário de crescimento nos últimos anos e que se reflete, principalmente,
naqueles que têm a impressão digital como forma de identificação. No que tange à segurança, sistemas baseados em
biometria necessitam da mesma preocupação que se tem com sistemas tradicionais de senhas e cartões. Neste contexto, o método Fuzzy Vault aparece para prover a segurança de sistemas biométricos, particularmente, protegendo a amostra biométrica armazenada. Esta pesquisa consiste na implementação do método Fuzzy Vault, aplicando-o para ocultar uma chave de 128 bits, onde o método será utilizado juntamente com algoritmos de código aberto, para o desenvolvimento de um aplicativo biométrico de impressões digitais, denominado por ABID. Serão expostas avaliações sobre o desempenho e segurança do aplicativo e também resultados experimentais comuns a sistemas biométricos, como: Taxa de Falso Aceite (FAR -False Accept Rate), Taxa de Aceite Genuíno (GAR-Genuine Accept Rate) e Taxa de Falsa Rejeição (FRR-False Rejection Rate).
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Falcão, Thiago Azevedo. "Comparação do desempenho do classificador de novidades com o classificador do vizinho mais próximo no reconhecimento facial." Universidade Federal do Amazonas, 2014. http://tede.ufam.edu.br/handle/tede/3297.
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Previous issue date: 2014-01-13<br>This work proposes the new classifier for face recognition, novelty classifier, which is based on novelty filter proposed by Kohonen. In order to evaluate the new classifier performance, it is performed a comparison with nearest neighboard classifier, which uses the Euclidian distance as distance metric. ORL face database was chosen to be used in this comparison. There was not any pre-processing (photometric or geometric) on face images. It was used the following feature extraction methods: PCA, 2DPCA and (2D)2PCA. Some results in identification mode are exposed through rank 1 recognition rate and CMC curves. In verification mode, the results were presented by Correct Acceptance Rate (CAR), Equivalent Error Rate (EER), ROC curves and Area under the ROC curve (AUC). Results shown that the proposed classifier performs better than others previously published, when the 10-fold Cross Validation method is employed as a test strategy. Recognition rate of 100% is achieved with this test methodology.<br>Este trabalho propõe a utilização do classificador de novidades para reconhecimento de faces, o qual é baseado no filtro de novidades, proposto por Kohonen. Para avaliar o desempenho do novo classificador é feita uma comparação com o classificador do vizinho mais próximo, usando a métrica da distância euclidiana. A base de dados utilizada para essa comparação foi a base ORL. A informação da face é extraída utilizando os métodos PCA, 2DPCA e (2D)2PCA, sem usar qualquer tipo de pré-processamento (fotométrico ou geométrico). Os seguintes resultados são apresentados no modo de identificação: taxa de reconhecimento rank 1 e as curvas CMC, no modo verificação: as taxas de correta aceitação (CAR), de erro equivalente (EER), as curvas ROC e área sob a curva ROC (AUC). Os resultados obtidos mostraram que o classificador proposto tem um desempenho melhor do que o desempenho do vizinho mais próximo e do que outros classificadores anteriormente publicados usando a mesma base, quando a estratégia de validação cruzada 10-fold é usada, com essa estratégia a taxa de reconhecimento obtida foi de 100%
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Alsolami, Eesa. "An examination of keystroke dynamics for continuous user authentication." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/54730/1/Eesa_Alsolami_Thesis.pdf.
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Most current computer systems authorise the user at the start of a session and do not detect whether the current user is still the initial authorised user, a substitute user, or an intruder pretending to be a valid user. Therefore, a system that continuously checks the identity of the user throughout the session is necessary without being intrusive to end-user and/or effectively doing this. Such a system is called a continuous authentication system (CAS).
Researchers have applied several approaches for CAS and most of these techniques are based on biometrics. These continuous biometric authentication systems (CBAS) are supplied by user traits and characteristics. One of the main types of biometric is keystroke dynamics which has been widely tried and accepted for providing continuous user authentication. Keystroke dynamics is appealing for many reasons. First, it is less obtrusive, since users will be typing on the computer keyboard anyway. Second, it does not require extra hardware. Finally, keystroke dynamics will be available after the authentication step at the start of the computer session.
Currently, there is insufficient research in the CBAS with keystroke dynamics field. To date, most of the existing schemes ignore the continuous authentication scenarios which might affect their practicality in different real world applications.
Also, the contemporary CBAS with keystroke dynamics approaches use characters sequences as features that are representative of user typing behavior but their selected features criteria do not guarantee features with strong statistical significance which may cause less accurate statistical user-representation. Furthermore, their selected features do not inherently incorporate user typing behavior. Finally, the existing CBAS that are based on keystroke dynamics are typically dependent on pre-defined user-typing models for continuous authentication. This dependency restricts the systems to authenticate only known users whose typing samples are modelled.
This research addresses the previous limitations associated with the existing CBAS schemes by developing a generic model to better identify and understand the characteristics and requirements of each type of CBAS and continuous authentication scenario. Also, the research proposes four statistical-based feature selection techniques that have highest statistical significance and encompasses different user typing behaviors which represent user typing patterns effectively. Finally, the research proposes the user-independent threshold approach that is able to authenticate a user accurately without needing any predefined user typing model a-priori.
Also, we enhance the technique to detect the impostor or intruder who may take over during the entire computer session.
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Ribeiro, Matheus Antônio Corrêa. "Gerenciamento e autenticação de identidades digitais usando feições faciais." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2008. http://hdl.handle.net/10183/15740.
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Em nossa vida diária, são utilizadas identidades digitais (IDDs) para acessar contas de e-mail, bancos e lojas virtuais, locais restritos, computadores compartilhados, e outros. Garantir que apenas usuários autorizados tenham o acesso permitido é um aspecto fundamental no desenvolvimento destas aplicações. Atualmente, os métodos de controle de acesso simples como senhas ou números de identificação pessoal não devem ser considerados suficientemente seguros, já que um impostor pode conseguir estas informações sem o conhecimento do usuário. Ainda, no caso de utilização de dispositivos físicos como cartões de identificação, estes podem ser roubados ou forjados. Para tornar estes sistemas mais confiáveis, técnicas de autenticação de identidades utilizando múltiplas verificações são propostas. A utilização de características biométricas surge como a alternativa mais confiável para tratar este problema, pois são, teoricamente, únicas para cada pessoa. Contudo, algumas características biométricas como a aparência facial podem variar com o tempo, implicando em um grande desafio para os sistemas de reconhecimento facial. Neste trabalho é combinado o acesso tradicional por senha com a análise da face para realizar a autenticação. Um método de aprendizagem supervisionada é apresentado e sua adaptação é baseada na melhora contínua dos modelos faciais, que são representados por misturas de gaussianas. Os resultados experimentais, obtidos sobre um conjunto de teste reduzido, são encorajadores, com 98% de identificação correta dos usuários e custo computacional relativamente baixo. Ainda, a comparação com um método apresentado na literatura indicou vantagens do método proposto quando usado como um pré-selecionador de faces.<br>In our daily life, we use digital identities (DIDs) to access e-mails, e-banks, e-shops, physical environments, shared computers, and so on. Guarantee that only authorized users are granted access is an important aspect in the development of such applications. Nowadays, the simple access control methods like passwords or personal identification numbers can not be considered secure enough, because an impostor can obtain and use these information without user knowledge. Also, physical devices like ID cards can be stolen. To make these systems more reliable, multimodal DID authentication techniques combining different verification steps are proposed. Biometric features appears as one of the most reliable alternatives to deal with this problem because, theoretically, they are unique for each person. Nevertheless, some biometric features like face appearances may change in time, posing a serious challenge for a face recognition system. In this thesis work, we use the traditional password access combined with human face analysis to perform the authentication task. An intuitive supervised appearance learning method is presented, and its adaptation is based on continuously improving face models represented using the Gaussian mixture modeling approach. The experimental results over a reduced test set show encouraging results, with 98% of the users correctly identified, with a relatively small computational effort. Still, the comparison with a method presented in the literature indicated advantages of the proposed method when used as a pre-selector of faces.
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LAUDATO, Gennaro. "Innovative information systems to monitor biomedical parameters during high demanding tasks." Doctoral thesis, Università degli studi del Molise, 2021. http://hdl.handle.net/11695/100496.
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The objective of this PhD project is, as its research core, the application of Machine Learning techniques and Big Data analytics to monitor, in a non-invasive way, vital parameters of individuals engaged in tasks that require a high psychophysical effort.
The industrial partners of this project are Formula Medicine (as Italian industrial partner with advisor Dr. Riccardo Ceccarelli) and AOTech (foreign industrial partner with advisor mr. Sebastien Philippe).
Formula Medicine is a sports medicine center able to offer medical assistance and training programs both physical and mental. Its strength is represented by the Mental Economy Gym, a gym dedicated to the optimization of mental resources. AOTech, on the other hand, is a partner company of Formula Medicine and a leader in the definition of high-tech products and services for the automotive industry and motorsport. AOTech has designed a sport driving simulator, able to reproduce all the main world circuits.
The simulator, thanks to the equipment of a hydraulic system, allows to relive physical and mental
sensations very similar to those perceived during real driving. The software system also allows vehicle’s data extraction.
Within the present project, also taking into account the research domain of the industrial partners, the focus has been addressed to the monitoring of athletes belonging to motorsport with two linked but distinct objectives: the first, strictly related to the analysis of the drivers’ body performances and the second dedicated to the automatic identification of cardiac pathologies starting from electrocardiographic data.
Finally, the know-how on the monitoring of biomedical parameters, acquired during the first years of this PhD project in the field of motorsport, was exported to the field of software engineering with the aim of verifying the possibility of predicting the correctness of a programming task that a software developer performs, based on the continuous monitoring of his body parameters.
As a first result of the PhD, novel metrics have been defined to objectify effort, physical consumption, stress, and other factors. These metrics have been included in the software in use in Formula Medicine to have a measure of performance. In addition, part of them were correlated with the race performance of the drivers, through the integration of the body data with the data derived from the driving simulator used in AOTech.
With regards to the second research focus, a decision support system was defined in the context of
early diagnosis of cardiac diseases. The recommendation system consists of several algorithms that accept as input a digital electrocardiographic lead and identify the presence of a possible cardiac pathology.
Finally, in the software engineering research field, the production of a developer was measured by evaluating the absence of defects in the source code.
Preliminary results show that the proposed approach—that takes into account biomedical and code-based features—allows to discriminate with fair accuracy the outcome of a programming task, reaching an accuracy higher than 80%.
This result was compared to state of the art metrics based on measures on the source code. It was higher than source code metrics, thus demonstrating the importance of biometric measurements in the identification of correctness of a coding task.
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Lodrová, Dana. "Bezpečnost biometrických systémů." Doctoral thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-261226.
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Hlavním přínosem této práce jsou dva nové přístupy pro zvýšení bezpečnosti biometrických systémů založených na rozpoznávání podle otisků prstů. První přístup je z oblasti testování živosti a znemožňuje použití různých typů falešných otisků prstů a jiných metod oklamání senzoru v průběhu procesu snímání otisků. Tento patentovaný přístup je založen na změně barvy a šířky papilárních linií vlivem přitlačení prstu na skleněný podklad. Výsledná jednotka pro testování živosti může být integrována do optických senzorů. Druhý přístup je z oblasti standardizace a zvyšuje bezpečnost a interoperabilitu procesů extrakce markantů a porovnání. Pro tyto účely jsem vytvořila metodologii, která stanovuje míry sémantické shody pro extraktory markantů otisků prstů. Markanty nalezené testovanými extraktory jsou porovnávány oproti Ground-Truth markantům získaným pomocí shlukování dat poskytnutých daktyloskopickými experty. Tato navrhovaná metodologie je zahrnuta v navrhovaném dodatku k normě ISO/IEC 29109-2 (Amd. 2 WD4).
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Ferrara, Matteo <1979>. "Biometric Fingerprint Recognition Systems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1234/1/TesiFinale_-_Matteo_Ferrara.pdf.
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Ferrara, Matteo <1979>. "Biometric Fingerprint Recognition Systems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1234/.
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Foltýn, Petr. "Návrh a realizace jednotek modulárního přístupového systému." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2010. http://www.nusl.cz/ntk/nusl-229208.
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Sanderson, Conrad, and conradsand@ieee org. "Automatic Person Verification Using Speech and Face Information." Griffith University. School of Microelectronic Engineering, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030422.105519.
Full textAbstract:
Identity verification systems are an important part of our every day life. A typical example is the Automatic Teller Machine (ATM) which employs a simple identity verification scheme: the user is asked to enter their secret password after inserting their ATM card; if the password matches the one prescribed to the card, the user is allowed access to their bank account. This scheme suffers from a major drawback: only the validity of the combination of a certain possession (the ATM card) and certain knowledge (the password) is verified. The ATM card can be lost or stolen, and the password can be compromised. Thus new verification methods have emerged, where the password has either been replaced by, or used in addition to, biometrics such as the persons speech, face image or fingerprints. Apart from the ATM example described above, biometrics can be applied to other areas, such as telephone & internet based banking, airline reservations & check-in, as well as forensic work and law enforcement applications. Biometric systems based on face images and/or speech signals have been shown to be quite effective. However, their performance easily degrades in the presence of a mismatch between training and testing conditions. For speech based systems this is usually in the form of channel distortion and/or ambient noise; for face based systems it can be in the form of a change in the illumination direction. A system which uses more than one biometric at the same time is known as a multi-modal verification system; it is often comprised of several modality experts and a decision stage. Since a multi-modal system uses complimentary discriminative information, lower error rates can be achieved; moreover, such a system can also be more robust, since the contribution of the modality affected by environmental conditions can be decreased. This thesis makes several contributions aimed at increasing the robustness of single- and multi-modal verification systems. Some of the major contributions are listed below. The robustness of a speech based system to ambient noise is increased by using Maximum Auto-Correlation Value (MACV) features, which utilize information from the source part of the speech signal. A new facial feature extraction technique is proposed (termed DCT-mod2), which utilizes polynomial coefficients derived from 2D Discrete Cosine Transform (DCT) coefficients of spatially neighbouring blocks. The DCT-mod2 features are shown to be robust to an illumination direction change as well as being over 80 times quicker to compute than 2D Gabor wavelet derived features. The fragility of Principal Component Analysis (PCA) derived features to an illumination direction change is solved by introducing a pre-processing step utilizing the DCT-mod2 feature extraction. We show that the enhanced PCA technique retains all the positive aspects of traditional PCA (that is, robustness to compression artefacts and white Gaussian noise) while also being robust to the illumination direction change. Several new methods, for use in fusion of speech and face information under noisy conditions, are proposed; these include a weight adjustment procedure, which explicitly measures the quality of the speech signal, and a decision stage comprised of a structurally noise resistant piece-wise linear classifier, which attempts to minimize the effects of noisy conditions via structural constraints on the decision boundary.
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Záleský, Jiří. "Rekonstrukce krevního řečiště prstu ve 3D z videosekvence." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417260.
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The goal of the master thesis is the design and construction of a device for capturing video sequences of the cardiovascular system of the finger of a human hand and the subsequently design and implementation of a method of data extraction for its reconstruction into a 3D model.
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Кондратенко, Н. Р., та О. А. Рудик. "Штучні імунні системи та їх використання для вирішення різних типів задач". Thesis, ВНТУ, 2019. http://ir.lib.vntu.edu.ua//handle/123456789/24236.
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У доповіді описано принцип роботи штучної імунної системи. Також розглянуто класи задач для рішення яких можуть бути використані відповідні системи задля обґрунтування доцільності використання штучної імунної системи для подальшої розробки засобу біометричної системи ідентифікації по особливостям клавіатурного почерку .<br>The article describes the principle of the artificial immune system. Also, classes of problems for the solution of which the appropriate systems can be used to justify the feasibility of using an artificial immune system for further development of a means of biometric identification system on the features of keyboard writing.