Relevant bibliographies by topics / Biometric data

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Biometric data'

Author: Grafiati
Published: 4 June 2021
Last updated: 28 May 2022

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Journal articles on the topic "Biometric data"

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Chinyemba, Melissa K., and Jackson Phiri. "Gaps in the Management and Use of Biometric Data: A Case of Zambian Public and Private Institutions." Zambia ICT Journal 2, no. 1 (June 29, 2018): 35–43. http://dx.doi.org/10.33260/zictjournal.v2i1.49.

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The current physical and cybersecurity systems rely on traditional three-factor authentication to mitigate the threats posed by insider attacks. Key is the use of biometric information. Biometrics are a unique measurement and analysis of the unique physiological special traits such as voice, eye structure and others that can be used in the discipline of varying person identification. Biometry, which is the analysis of these biometrics is a complex process but guarantees identification and non-repudiation. If used to identify humans then several issues such as where is the biometric data stored? Who has access to it? And how does one ensure that such data satisfies the principle of availability. To achieve availability, secure transportation arises. To achieve transportation, non-repudiation, confidentiality and authentication, integrity arise. A storage and transport system is recommended to these challenges. In this paper, we explore the gaps into how public and private institution store and manage biometrics information. We benchmarked each organization again the ISO 30107 and ISO 24745. Our results show that while most companies are adopting and using biometrics systems, few have adopted the ISO biometrics standards that govern the storage and management of biometric information and hence creating security risk.
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Alam*, Varisha, and Dr Mohammad Arif. "Classification of Large Biometric Data in Database System." International Journal of Innovative Technology and Exploring Engineering 10, no. 10 (August 30, 2021): 1–8. http://dx.doi.org/10.35940/ijitee.d8592.08101021.

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"Biometrics" is got from the Greek word 'life' and 'measure' which implies living and evaluation take apart. It simply converts into "life estimation". Biometrics uses computerized acknowledgment of people, dependent on their social and natural attributes. Biometric character are data separated from biometric tests, which can use for examination with a biometric orientation. Biometrics involves techniques to unusually recognize people dependent on at least one inherent physical or behavior attribute. In software engineering, specifically, biometric is used as a form of character retrieve the Committee and retrieve command. Biometric identically utilized to recognize people in bunches that are in observation. Biometric has quickly risen like a auspicious innovation for validation and has effectively discovered a spot in most of the scientific safety regions. An effective bunching method suggest for dividing enormous biometrics data set through recognizable proof. This method depends on the changed B+ tree is decreasing the discs get to. It diminishes the information recovery time and also possible error rates. Hence, for bigger applications, the need to reduce the data set to a more adequate portion emerges to accomplish both higher paces and further developed precision. The main motivation behind ordering is to recover a small data set for looking through the inquiry
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RODRIGUES, Paulo Canas, Luiz Ricardo NAKAMURA, and Carlos Alberto de Bragança PEREIRA. "SPECIAL ISSUE ON BIOSTATISTICS AND BIOMETRY IN THE ERA OF DATA SCIENCE." REVISTA BRASILEIRA DE BIOMETRIA 39, no. 1 (March 30, 2021): 1–6. http://dx.doi.org/10.28951/rbb.v39i1.556.

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This special issue of the Brazilian Journal of Biometrics (BJB) contains 16 papers. The main topic of the special issue is "Biostatistics and Biometry in the Era of Data Science", and it is the result of a collaboration between the BJB and the Brazilian Region of the International Biometric Society (RBras) in the sequence of the cancelled 2020 RBras annual meeting due to the COVID-19 pandemic.
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Jacobsen, Katja Lindskov. "Biometric data flows and unintended consequences of counterterrorism." International Review of the Red Cross 103, no. 916-917 (April 2021): 619–52. http://dx.doi.org/10.1017/s1816383121000928.

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AbstractExamining unintended consequences of the makings and processing of biometric data in counterterrorism and humanitarian contexts, this article introduces a two-fold framework through which it analyzes biometric data-makings and flows in Afghanistan and Somalia. It combines Tilley's notion of “living laboratory” and Larkin's notion of infrastructure into a framework that attends to the conditions under which biometric data is made and to subsequent flows of such data through data-sharing agreements or unplanned access. Exploring such unintended consequences, attention needs to be paid to the variety of actors using biometrics for different purposes yet with data flows across such differences. Accordingly, the article introduces the notion of digital intervention infrastructures, with biometric databases as one dimension.
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Srivastava, Prateek, and Rohit Srivastava. "A Multimodal Based Approach for Face and Unique Mark Based Combination for Confirmation of Human." International Journal of Business Analytics 6, no. 3 (July 2019): 16–28. http://dx.doi.org/10.4018/ijban.2019070102.

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Biometric processes are utilized for recognition and distinguishing a person for different applications. The procedure is made possible by utilizing single biometric highlight or a mix of biometric highlights. In the event that the distinguishing proof is finished by utilizing a solitary biometric highlight (confront, iris, finger, palm, and so forth) then the framework is called unimodal, and if a combnation of biometrics are utilized then it is called multimodal. In a multimodal framework compared to the different downsides of a unimodal framework (noisy data, multiple vectors and so forth) are evacuated. The fundamental objective of the proposed work is to outline a system that will give validation in view of three-level verification for a man. Prior works in this field are clarified in various factual models in view of various verification plans. In the proposed strategy, a system is created in which if one biometric attribute fails then the other biometic characteristics can be utilized for verification.
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Rassolov, I. M., S. G. Chubukova, and I. V. Mikurova. "Biometrics in the Context of Personal Data and Genetic Information: Legal Issues." Lex Russica, no. 1 (January 1, 2019): 108–18. http://dx.doi.org/10.17803/1729-5920.2019.146.1.108-118.

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In modern society, methods of identification of persons on the basis of their physical, biological or behavioral characteristics are actively developing. European countries are in the process of developing a holistic doctrine on biometric control and are clarifying their position on situations where biometric data are used by individuals.From the position of information law, the paper presents a new author’s approach to the problem of processing biometric data and genetic information. The division of biometrics into “trace” and “non-trace” is losing its meaning. A new classification of biometrics into digital and analog is proposed.Biometric access control should not become a routine phenomenon in the framework of the organization of the company and without any reason to replace other existing types of control. The interested person can be entrusted with the storage of their own biometric data to reduce the risks of leakage and the consequences of exposure to them. Biometric data must be stored on the company’s servers in encrypted form, which makes it impossible to use them without the consent of the person concerned.Biometric data should be protected by a special legal regime. The analysis of the European and Russian legislation made it possible to draw the following conclusions: biometric data is a special type of personal data, a special legal regime and regulation should be established; digital biometrics needs special legal regulation, since it is the most vulnerable type; genetic information does not fully correspond to the concept of personal data, as it can relate to an unlimited number of persons. This determines the need to develop a special law “on genetic information”.
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Bok, Jin Yeong, Kun Ha Suh, and Eui Chul Lee. "Detecting Fake Finger-Vein Data Using Remote Photoplethysmography." Electronics 8, no. 9 (September 11, 2019): 1016. http://dx.doi.org/10.3390/electronics8091016.

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Today, biometrics is being widely used in various fields. Finger-vein is a type of biometric information and is based on finger-vein patterns unique to each individual. Various spoofing attacks have recently become a threat to biometric systems. A spoofing attack is defined as an unauthorized user attempting to deceive a system by presenting fake samples of registered biometric information. Generally, finger-vein recognition, using blood vessel characteristics inside the skin, is known to be more difficult when producing counterfeit samples than other biometrics, but several spoofing attacks have still been reported. To prevent spoofing attacks, conventional finger-vein recognition systems mainly use the difference in texture information between real and fake images, but such information may appear different depending on the camera. Therefore, we propose a method that can detect forged finger-vein independently of a camera by using remote photoplethysmography. Our main idea is to get the vital sign of arterial blood flow, a biometric measure indicating life. In this paper, we selected the frequency spectrum of time domain signal obtained from a video, as the feature, and then classified data as real or fake using the support vector machine classifier. Consequently, the accuracy of the experimental result was about 96.46%.
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Sridevi, T., P. Mallikarjuna Rao, and P. V. Ramaraju. "Wireless sensor data mining for e-commerce applications." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 1 (December 25, 2018): 462. http://dx.doi.org/10.11591/ijeecs.v14.i1.pp462-470.

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Information hiding is the most important criteria today in several sectors, due to security issues. Mostly for the security applications used in Finance & banking sectors, hiding the information about users and their transactions are necessary at present from the hackers in all high security zones. In this consequence biometrics is progressively considered as foundation component for an extensive array of personal authentication solutions, both at the national level (E.g. India UIDAI) and the smaller-scale (E.g. banking ATMs, school lunch payment systems). Biometric fraud is also an area of increasing concern, as the number of deployed biometric systems increases and fraudsters become aware of the potential to compromise them. Organizations are increasingly deploying process and technology solutions to stay one step ahead. At present Bankers are using different single Biometric Modalities for different services. All Biometric features are not suitable, for all services because of various artifacts while extracting features from the sensors due to background noise, lighting conditions, ease of access etc. This paper proposes a multi model system that will show a onetime single solution to meet all their security problems. This paper particularly handles how to incorporate cryptography and steganography in biometric applications.
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Hidayat, Taopik, Nurul Khasanah, Daniati Uki Eka Saputri, Umi Khultsum, and Risca Lusiana Pratiwi. "Klasifikasi Gambar Palmprint Berbasis Multi-Kelas Menggunakan Convolutional Neural Network." Jurnal Sistem Informasi 11, no. 1 (February 26, 2022): 01–06. http://dx.doi.org/10.51998/jsi.v11i1.474.

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Abstract—Biometric technology is developing to be the most relevant mechanism in identity identification. The main purpose of an identity management system is to be able to establish a relationship between individuals and their identities when needed under certain conditions. Among the newly proposed identity verification and personal identification technologies, biometrics is rapidly becoming the most relevant mechanism for identity recognition. This study proposes a new biometric recognition method for authentication and personal identification. Palm image recognition based on image processing for authentication and personal identification is proposed, namely competitive coding using the Convolutional Neural Network (CNN) and Local Binary Pattern (LBP) texture extraction with hyperparameter modifications. The dataset used comes from the Birjand University Mobile Palmprint Database (BMPD) which consists of 20 classes with a total of 800 palm images. The research was conducted using a data distribution of 80% training data and 20% validation data. The tests carried out resulted in a good accuracy value of the proposed model of 93.3% for the training process and 90.6% for the validation process. Keywords: Biomethric, CNN, LBP Intisari— Teknologi biometrik berkembang menjadi mekanisme paling relevan dalam pengidentifikasi identitas. Tujuan utama dari sistem manajemen identitas adalah untuk dapat membangun hubungan antara individu dan identitas mereka ketika dibutuhkan dalam kondisi tertentu. Di antara verifikasi identitas yang baru diusulkan dan teknologi identifikasi pribadi, biometrik dengan cepat menjadi mekanisme yang paling relevan untuk pengenalan identitas. Penelitian ini mengusulkan metode pengenalan biometrik terbaru untuk otentikasi dan identifikasi pribadi. Pengenalan citra telapak tangan berbasis image processing untuk otentikasi dan identifikasi pribadi yang diusulkan yaitu pengkodean kompetitif menggunakan metode Convolutional Neural Network (CNN) dan ekstraksi tekstur Local Binary Pattern (LBP) dengan modifikasi hyperparameter. Dataset yang digunakan berasal dari Birjand University Mobile Palmprint Database(BMPD) yang terdiri dari 20 kelas dengan total 800 citra telapak tangan. Penelitian dilakukan dengan menggunakan distribusi data sebesar 80% data training dan 20% data validasi. Pengujian yang dilakukan menghasilkan nilai akurasi yang baik dari model yang diusulkan sebesar 93,3% untuk proses training dan 90,6% untuk proses validasi. Kata Kunci: Biometrik, CNN, LBP
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Lakhera, Manmohan, and Manmohan Singh Rauthan. "Securing Stored Biometric Template Using Cryptographic Algorithm." International Journal of Rough Sets and Data Analysis 5, no. 4 (October 2018): 48–60. http://dx.doi.org/10.4018/ijrsda.2018100103.

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The biometric template protection technique provides the security in many authentication applications. Authentication based on biometrics has more advantages over traditional methods such as password and token-based authentication methods. The advantage of any biometric-based authentication system over a traditional one is that the person must physically be present at that place while recognizing him. So, it is essential to secure these biometrics by combining these with cryptography. In the proposed algorithm, the AES algorithm is used for securing the stored and transmitted biometric templates using helping data. The helping data is a variable type of data which is changed at every attempt for registration. The final symmetric key AES algorithm is a combination of helping data and actual symmetric keys of the AES algorithm. The experimental analysis shows that a brute force attack takes a long time to recover the original biometric template from cipher biometric template. So, the proposed technique provides sufficient security to stored biometric templates.
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Dissertations / Theses on the topic "Biometric data"

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McNulty, Peggy Sue. "Values issues in biometric data collection." Connect to Electronic Thesis (CONTENTdm), 2009. http://worldcat.org/oclc/525070842/viewonline.

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Ugail, Hassan, and Eyad Elyan. "Efficient 3D data representation for biometric applications." IOS Press, 2007. http://hdl.handle.net/10454/2683.

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Yes
An important issue in many of today's biometric applications is the development of efficient and accurate techniques for representing related 3D data. Such data is often available through the process of digitization of complex geometric objects which are of importance to biometric applications. For example, in the area of 3D face recognition a digital point cloud of data corresponding to a given face is usually provided by a 3D digital scanner. For efficient data storage and for identification/authentication in a timely fashion such data requires to be represented using a few parameters or variables which are meaningful. Here we show how mathematical techniques based on Partial Differential Equations (PDEs) can be utilized to represent complex 3D data where the data can be parameterized in an efficient way. For example, in the case of a 3D face we show how it can be represented using PDEs whereby a handful of key facial parameters can be identified for efficient storage and verification.
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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.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 81).
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.
by Lawrence G. Lam.
S.M. in Engineering and Management
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Stevenson, Brady Roos. "Analysis of Near-Infrared Phase Effects on Biometric Iris Data." BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/1299.

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The purpose of this research is to ascertain potential iris scan data variations from near infrared waves derived from fluorescent illumination. Prior studies of iris data variances from infrared wave interference of halogen, incandescent, and sunlight with iris cameras suggest that similar changes may exist under near infrared wavelengths from fluorescent light. The concern is that the fluorescent energy emission may interfere with the near infrared detection of an iris camera. An iris camera is used to measure human eye characteristics known as biometrics. If such infrared emission is statistically significant, then it can alter the validity of the iris scan data. The experiment utilized nine hundred forty-five (945) scans from sixty-three (63) subjects. Measured results showed increased heat from ambient fluorescent illumination does not statistically alter the biometric readings of human eyes. The test results fail to reject that data loss will not occur as heat is increased in the ambient fluorescent light source.
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Khanna, Tania. "Low power data acquisition for microImplant biometric monitoring of tremors." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/78448.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 97-100).
In recent years, trends in the medical industry have created a growing demand for implantable medical devices. In particular, the need to provide doctors a means to continuously monitor biometrics over long time scales with increased precision is paramount to efficient healthcare. To make medical implants more attractive, there is a need to reduce their size and power consumption. Small medical implants would allow for less invasive procedures, greater comfort for patients, and increased patient compliance. Reductions in power consumption translate to longer battery life. The two primary limitations to the size of small medical implants are the batteries that provide energy to circuit and sensor components and the antennas that enable wireless communication to terminals outside of the body. The theory is applied in the context of the long term monitoring of Parkinson's tremors. This work investigates how to reduce the amount of data needing to acquire a signal by applying compressive sampling thereby alleviating the demand on the energy source. A low energy SAR ADC is designed using adiabatic charging to further reduce energy usage. This application is ideal for adiabatic techniques because of the low frequency of operation and the ease with which we can reclaim energy from discharging the capacitors. Keywords: SAR ADC, adiabatic, compressive sampling, biometric, implants
by Tania Khanna.
Ph.D.
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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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Pisani, Paulo Henrique. "Biometrics in a data stream context." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-08052017-141153/.

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The growing presence of the Internet in day-to-day tasks, along with the evolution of computational systems, contributed to increase data exposure. This scenario highlights the need for safer user authentication systems. An alternative to deal with this is by the use of biometric systems. However, biometric features may change over time, an issue that can affect the recognition performance due to an outdated biometric reference. This effect can be called as template ageing in the area of biometrics and as concept drift in machine learning. It raises the need to automatically adapt the biometric reference over time, a task performed by adaptive biometric systems. This thesis studied adaptive biometric systems considering biometrics in a data stream context. In this context, the test is performed on a biometric data stream, in which the query samples are presented one after another to the biometric system. An adaptive biometric system then has to classify each query and adapt the biometric reference. The decision to perform the adaptation is taken by the biometric system. Among the biometric modalities, this thesis focused on behavioural biometrics, particularly on keystroke dynamics and on accelerometer biometrics. Behavioural modalities tend to be subject to faster changes over time than physical modalities. Nevertheless, there were few studies dealing with adaptive biometric systems for behavioural modalities, highlighting a gap to be explored. Throughout the thesis, several aspects to enhance the design of adaptive biometric systems for behavioural modalities in a data stream context were discussed: proposal of adaptation strategies for the immune-based classification algorithm Self-Detector, combination of genuine and impostor models in the Enhanced Template Update framework and application of score normalization to adaptive biometric systems. Based on the investigation of these aspects, it was observed that the best choice for each studied aspect of the adaptive biometric systems can be different depending on the dataset and, furthermore, depending on the users in the dataset. The different user characteristics, including the way that the biometric features change over time, suggests that adaptation strategies should be chosen per user. This motivated the proposal of a modular adaptive biometric system, named ModBioS, which can choose each of these aspects per user. ModBioS is capable of generalizing several baselines and proposals into a single modular framework, along with the possibility of assigning different adaptation strategies per user. Experimental results showed that the modular adaptive biometric system can outperform several baseline systems, while opening a number of new opportunities for future work.
A crescente presença da Internet nas tarefas do dia a dia, juntamente com a evolução dos sistemas computacionais, contribuiu para aumentar a exposição dos dados. Esse cenário evidencia a necessidade de sistemas de autenticação de usuários mais seguros. Uma alternativa para lidar com isso é pelo uso de sistemas biométricos. Contudo, características biométricas podem mudar com o tempo, o que pode afetar o desempenho de reconhecimento devido a uma referência biométrica desatualizada. Esse efeito pode ser chamado de template ageing na área de sistemas biométricos adaptativos ou de mudança de conceito em aprendizado de máquina. Isso levanta a necessidade de adaptar automaticamente a referência biométrica com o tempo, uma tarefa executada por sistemas biométricos adaptativos. Esta tese estudou sistemas biométricos adaptativos considerando biometria em um contexto de fluxo de dados. Neste contexto, o teste é executado em um fluxo de dados biométrico, em que as amostras de consulta são apresentadas uma após a outra para o sistema biométrico. Um sistema biométrico adaptativo deve então classificar cada consulta e adaptar a referência biométrica. A decisão de executar a adaptação é tomada pelo sistema biométrico. Dentre as modalidades biométricas, esta tese foca em biometria comportamental, em particular em dinâmica da digitação e em biometria por acelerômetro. Modalidades comportamentais tendem a ser sujeitas a mudanças mais rápidas do que modalidades físicas. Entretanto, havia poucos estudos lidando com sistemas biométricos adaptativos para modalidades comportamentais, destacando uma lacuna para ser explorada. Ao longo da tese, diversos aspectos para aprimorar o projeto de sistemas biométricos adaptativos para modalidades comportamentais em um contexto de fluxo de dados foram discutidos: proposta de estratégias de adaptação para o algoritmo de classificação imunológico Self-Detector, combinação de modelos genuíno e impostor no framework do Enhanced Template Update e aplicação de normalização de scores em sistemas biométricos adaptativos. Com base na investigação desses aspectos, foi observado que a melhor escolha para cada aspecto estudado dos sistemas biométricos adaptativos pode ser diferente dependendo do conjunto de dados e, além disso, dependendo dos usuários no conjunto de dados. As diferentes características dos usuários, incluindo a forma como as características biométricas mudam com o tempo, sugerem que as estratégias de adaptação deveriam ser escolhidas por usuário. Isso motivou a proposta de um sistema biométrico adaptativo modular, chamado ModBioS, que pode escolher cada um desses aspectos por usuário. O ModBioS é capaz de generalizar diversos sistemas baseline e propostas apresentadas nesta tese em um framework modular, juntamente com a possibilidade de atribuir estratégias de adaptação diferentes por usuário. Resultados experimentais mostraram que o sistema biométrico adaptativo modular pode superar diversos sistemas baseline, enquanto que abre um grande número de oportunidades para trabalhos futuros.
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Pratt, Jamie M. "The Effects of Worksite Health Promotion Programs on Employee Biometric Data." BYU ScholarsArchive, 2014. https://scholarsarchive.byu.edu/etd/5752.

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INTRODUCTION: Worksite health promotion programs (WHPP) promote maintenance and changes of health-related behaviors of employees. Some companies opt to contract with a third party provider to implement a WHPP. PURPOSE: This study evaluated the participation rates, availability and use of health coaching, and changes in biometric data over a 2-year time period of employees in 13 companies for whom the WHPP was implemented by Wellness Corporate Solutions (WCS). METHODS: We had 2 years of biometric, health risk appraisal (HRA), or health coaching data on 4,473 employees. The statistical analysis included biometric screening data (percent body fat, body mass index (BMI), total cholesterol (TC), high- and low-density lipoproteins (HDL-C, LDL-C), TC/HDL ratio, triglycerides, glucose, systolic and diastolic blood pressures (SBP and DBP)) from all 13 companies and health coaching data from five companies. RESULTS: Employee participation rates of the 13 companies ranged from 35% to 75%. Five of the 13 companies provided voluntary telephonic health coaching to employees participating in their WHPPs. Of those employees for which we had 2-year data, 125 (12.9%) actually participated in health coaching. Only one of the 13 companies demonstrated improvement in all 10 biometric measurements and 1 company demonstrated improvement in only one biometric measurement. The biometric measurements that showed the greatest improvements over time were triglycerides, blood pressure, BMI, and TC. There was no association found between the number of variables that improved and employee participation rate (p = 0.8814) or the type of incentives offered to employees (p = 0.1389). Availability and use of health coaching did not appear to affect the number of variables that improved. Compared to employees who did not use health coaching, there were significantly greater changes in DBP, HDL-C, and BMI (p < 0.05) in employees who used health coaching. The magnitude of change in variables of interest was dependent, in part, on the baseline value. CONCLUSIONS: Voluntary participation in WHPPs results in positive changes in health-related biometric variables. Health coaching can positively affect the magnitude of change in some biometric variables and the magnitude of change is likely related to the baseline value and the frequency of coaching interactions. Further research should evaluate the benefits of various forms and frequencies of health coaching. Worksite health promotion programs and health coaching may also have a positive impact on other variables (e.g., employee attitudes and morale) not addressed in this study.
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Aronsson, Erik. "Biometric Authentication and Penetration of Smartphones." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-37713.

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This study aims to examine the function and vulnerabilities of biometric systemsintegrated in smartphones, as well as techniques for circumventing the securityof these systems. These techniques are then used against a selection of smart-phones in order to gauge the resilience of their biometric security. The function,vulnerabilities, and techniques associated with these systems are compiled usinga literature study of published papers and books on the subject. The performedexperiments apply these techniques in the form of presentation attacks directed atthe fingerprint-, face- and iris recognition systems of the examined smartphones.The result of the experiments showed significant differences between the differentsmartphones, where some exhibited flawless security and others showed significantsecurity flaws. Both fingerprint and face recognition systems were successfullycircumvented, while none of the iris recognition systems were breached. No clearlink could be observed between the cost of the device and success rate of attacks,while only devices using the Android operating system were breached. The resultsundeniably showed that some smartphones are vulnerable to the employed tech-niques. It also showed that some of the tested devices had managed to implementmeasures to counteract the applied presentation attacks. The root cause of thevulnerabilities showcased in the experiment is due to the fact that biometric traitscan be copied and reproduced, highlighting a basic flaw of such systems.
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Sinsel, Adam R. "Supporting the maritime information dominance: optimizing tactical network for biometric data sharing in maritime interdiction operations." Thesis, Monterey, California: Naval Postgraduate School, 2015. http://hdl.handle.net/10945/45257.

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Approved for public release; distribution is unlimited
This research intends to improve information dominance in the maritime domain by optimizing tactical mobile ad hoc network (MANET) systems for wireless sharing of biometric data in maritime interdiction operations (MIO). Current methods for sharing biometric data in MIO are unnecessarily slow and do not leverage wireless networks at the tactical edge to maximize information dominance. Field experiments allow students to test wireless MANETs at the tactical edge. Analysis is focused on determining optimal MANET design and implementation. It considers various implementations with varied antenna selection, radio power, and frequency specifications, and two specific methods of integrating Department of Defense biometric collection devices to the wireless MANET, which utilizes a single (WR) MPU4 802.11 Wi-Fi access point to connect secure electronic enrollment kit II (SEEK II) biometric devices to the MANET, and tethers each SEEK device to a dedicated WR using a personal Ethernet connection. Biometric data is shared across the tactical network and transmitted to remote servers. Observations and analysis regarding network performance demonstrate that wireless MANETs can be optimized for biometric reach back and integrated with biometric devices to improve biometric data sharing in MIO.
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Books on the topic "Biometric data"

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Dunstone, Ted, and Neil Yager, eds. Biometric System and Data Analysis. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-77627-9.

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Conti, Massimo, Natividad Martínez Madrid, Ralf Seepold, and Simone Orcioni, eds. Mobile Networks for Biometric Data Analysis. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39700-9.

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Neil, Yager, ed. Biometric system and data analysis: Design, evaluation, and data mining. New York: Springer, 2009.

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National Research Council (U.S.). Whither Biometrics Committee, ed. Biometric recognition: Challenges and opportunities. Washington, D.C: National Academies Press, 2010.

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Kindt, Els J. Privacy and Data Protection Issues of Biometric Applications. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7522-0.

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Levush, Ruth. Biometric data retention for passport applicants and holders. Washington, D.C.]: The Law Library of Congress, Global Legal Research Center, 2014.

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Bilan, Stepan, Mohamed Elhoseny, and D. Jude Hemanth, eds. Biometric Identification Technologies Based on Modern Data Mining Methods. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-48378-4.

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Continuous authentication using biometrics: Data, models, and metrics. Hershey, PA: Information Science Reference, 2012.

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Israel. Biometric means of identification: Complete translation of the new Law for the Inclusion of Biometric Means of Identification and Biometric Identity Data in Identity Documents and in a Data Base 5770-2009. Haifa, Israel: Aryeh Greenfield-A.G. Publications, 2010.

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Modi, Shimon K. Biometrics in identity management: Concepts to applications. Boston: Artech House, 2011.

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Book chapters on the topic "Biometric data"

1

Wingard, Melissa. "Bolstering Biometric Data." In Digital Transformation in a Post-COVID World, 245–62. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003148715-13.

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Li, Xiang, Jinyu Gao, Xiaobin Chang, Yuting Mai, and Wei-Shi Zheng. "Person Re-identification with Data-Driven Features." In Biometric Recognition, 506–13. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12484-1_58.

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Kevenaar, Tom. "Protection of Biometric Information." In Security with Noisy Data, 169–93. London: Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-984-2_11.

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Huang, Qianying, Yunsong Wu, Chenqiu Zhao, Xiaohong Zhang, and Dan Yang. "Category Guided Sparse Preserving Projection for Biometric Data Dimensionality Reduction." In Biometric Recognition, 539–46. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46654-5_59.

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Luo, Peng, Jinye Peng, Ziyu Guan, and Jianping Fan. "Hybrid Manifold Regularized Non-negative Matrix Factorization for Data Representation." In Biometric Recognition, 564–74. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46654-5_62.

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Ratha, Nalini K., Miguel A. Figueroa-Villanueva, Jonathan H. Connell, and Ruud M. Bolle. "A Secure Protocol for Data Hiding in Compressed Fingerprint Images." In Biometric Authentication, 205–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25976-3_19.

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Akula, Abhilash, Jeshwanth Ega, Kalyan Thota, and Gowtham. "Biometric Voting System." In Lecture Notes on Data Engineering and Communications Technologies, 231–35. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-24643-3_28.

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Yuan, Yunhao, Peng Lu, Zhiyong Xiao, Jianjun Liu, and Xiaojun Wu. "A Novel Supervised CCA Algorithm for Multiview Data Representation and Recognition." In Biometric Recognition, 702–9. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25417-3_82.

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Dong, Jianmin, and Zhongmin Cai. "User Authentication Using Motion Sensor Data from Both Wearables and Smartphones." In Biometric Recognition, 756–64. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46654-5_83.

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Gupta, Rahul, Naman Gupta, Tushar Gupta, Aditya Srivastava, Ritu Gupta, and Abhilasha Singh. "Gait Recognition Biometric System." In Proceedings of Data Analytics and Management, 29–40. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6289-8_4.

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Conference papers on the topic "Biometric data"

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Pisani, Paulo Henrique, and André C. P. L. F. De Carvalho. "Biometrics in a data stream context." In XXXI Concurso de Teses e Dissertações da SBC. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/ctd.2018.3650.

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Biometric systems can provide safer authentication. However, biometric features may change over time, impacting the recognition performance due to outdated biometric references. It raises the need to automatically adapt the references over time, by using adaptive biometric systems. This thesis studied several aspects of adaptive biometric systems in a data stream context. Based on this investigation, it was observed that the best choice for each aspect can be user dependent. This motivated the proposal of a modular adaptive biometric system, which can select a different configuration for each user. It also generalizes several baselines and proposals into a single modular framework, while opening numerous opportunities for future work.
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Vielhauer, Claus, and Ton Kalker. "Security for biometric data." In Electronic Imaging 2004, edited by Edward J. Delp III and Ping W. Wong. SPIE, 2004. http://dx.doi.org/10.1117/12.528261.

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Kocherov, Y. N., D. V. Samoylenko, and E. E. Tikhonov. "Safe Storage of Biometric Data." In 2020 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon). IEEE, 2020. http://dx.doi.org/10.1109/fareastcon50210.2020.9271161.

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Bringer, Julien, and Hervé Chabanne. "Negative databases for biometric data." In the 12th ACM workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1854229.1854242.

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De A. S. M., Juliana, and Márjory Da Costa-Abreu. "An evaluation of a three-modal hand-based database to forensic-based gender recognition." In Simpósio Brasileiro de Segurança da Informação e de Sistemas Computacionais. Sociedade Brasileira de Computação, 2019. http://dx.doi.org/10.5753/sbseg.2019.13989.

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In recent years, behavioural soft-biometrics have been widely used to improve biometric systems performance. Information like gender, age and ethnicity can be obtained from more than one behavioural modality. In this paper, we propose a multimodal hand-based behavioural database for gender recognition. Thus, our goal in this paper is to evaluate the performance of the multimodal database. For this, the experiment was realised with 76 users and was collected keyboard dynamics, touchscreen dynamics and handwritten signature data. Our approach consists of compare two-modal and one-modal modalities of the biometric data with the multimodal database. Traditional and new classifiers were used and the statistical Kruskal-Wallis to analyse the accuracy of the databases. The results showed that the multimodal database outperforms the other databases.
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Lakhera, Manmohan. "Enhancing security of stored biometric data." In 2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH). IEEE, 2014. http://dx.doi.org/10.1109/cipech.2014.7019043.

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Lionnie, Regina, Said Attamimi, Wahju Sediono, and Mudrik Alaydrus. "Biometric Identification with Limited Data Set." In 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS). IEEE, 2018. http://dx.doi.org/10.1109/eeccis.2018.8692859.

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Antal, Margit, and Gyozo Nemes. "Gender recognition from mobile biometric data." In 2016 IEEE 11th International Symposium on Applied Computational Intelligence and Informatics (SACI). IEEE, 2016. http://dx.doi.org/10.1109/saci.2016.7507379.

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Özkaynak, Fatih. "From Biometric Data to Cryptographic Primitives." In the 2017 International Conference. New York, New York, USA: ACM Press, 2017. http://dx.doi.org/10.1145/3143344.3143355.

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Handa, Jigyasa, Saurabh Singh, and Shipra Saraswat. "Approaches of Behavioural Biometric Traits." In 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence). IEEE, 2019. http://dx.doi.org/10.1109/confluence.2019.8776905.

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Reports on the topic "Biometric data"

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Wilson, C. L., P. J. Grother, and R. Chandramouli. Biometric data specification for personal identity verification. Gaithersburg, MD: National Institute of Standards and Technology, 2005. http://dx.doi.org/10.6028/nist.sp.800-76.

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Wilson, C. L., P. J. Grother, and R. Chandramouli. Biometric data specification for personal identity verification. Gaithersburg, MD: National Institute of Standards and Technology, 2007. http://dx.doi.org/10.6028/nist.sp.800-76-1.

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Podio, Fernando L., Dylan Yaga, and Christofer J. McGinnis. BioCTS 2012: Advanced Conformance Test Architectures and Test Suites for Biometric Data Interchange Formats and Biometric Information Records. Gaithersburg, MD: National Institute of Standards and Technology, September 2012. http://dx.doi.org/10.6028/nist.ir.7877.

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Podio, Fernando L., Dylan Yaga, and Mark Jerde. Conformance test architecture for biometric data interchange formats - version beta 2.0. Gaithersburg, MD: National Institute of Standards and Technology, 2011. http://dx.doi.org/10.6028/nist.ir.7771.

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Bossuroy, Thomas, Clara Delavallade, and Vincent Pons. Biometric Tracking, Healthcare Provision, and Data Quality: Experimental Evidence from Tuberculosis Control. Cambridge, MA: National Bureau of Economic Research, October 2019. http://dx.doi.org/10.3386/w26388.

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Wu, Jin Chu, and Charles L. Wilson. Using Chebyshev's inequality to determine sample size in biometric evaluation of fingerprint data. Gaithersburg, MD: National Institute of Standards and Technology, 2005. http://dx.doi.org/10.6028/nist.ir.7273.

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Cheng, Su Lan, Ross J. Micheals, and Z. Q. John Lu. Comparison of confidence intervals for large operational biometric data by parametric and non-parametric methods. Gaithersburg, MD: National Institute of Standards and Technology, 2010. http://dx.doi.org/10.6028/nist.ir.7740.

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Newton, Elaine, Gerry Coleman, and Patrice Yuh. Information systems-data format for the interchange of fingerprint, facial, & other biometric information- part 2 :. Gaithersburg, MD: National Institute of Standards and Technology, 2008. http://dx.doi.org/10.6028/nist.sp.500-275.

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Podio, Fernando L., Dylan Yaga, and Christofer J. McGinnis, eds. Conformance Testing Methodology for ANSI/NIST-ITL 1-2011, Data Format for the Interchange of Fingerprint, Facial and Other Biometric Information (Release 1.0). Gaithersburg, MD: National Institute of Standards and Technology, August 2012. http://dx.doi.org/10.6028/nist.sp.500-295.

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Wing, Bradford J. Data Format for the Interchange of Fingerprint, Facial and Other Biometric Information ANSI/NIST-ITL 1-2011 NIST Special Publication 500-290 Edition 2. National Institute of Standards and Technology, August 2013. http://dx.doi.org/10.6028/nist.sp.500-290e2.

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