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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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Anil K. Jain and U. Uludag. "Hiding biometric data." IEEE Transactions on Pattern Analysis and Machine Intelligence 25, no. 11 (November 2003): 1494–98. http://dx.doi.org/10.1109/tpami.2003.1240122.
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Dabas, Ashish, Ms Shalini Bhadola, and Ms Kirti Bhatia. "Storage of Biometric Data in Database." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (April 30, 2019): 1001–4. http://dx.doi.org/10.31142/ijtsrd23146.
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S. Raju, A., and V. Udayashankara. "A Survey on Unimodal, Multimodal Biometrics and Its Fusion Techniques." International Journal of Engineering & Technology 7, no. 4.36 (December 9, 2018): 689. http://dx.doi.org/10.14419/ijet.v7i4.36.24224.
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Presently, a variety of biometric modalities are applied to perform human identification or user verification. Unimodal biometric systems (UBS) is a technique which guarantees authentication information by processing distinctive characteristic sequences and these are fetched out from individuals. However, the performance of unimodal biometric systems restricted in terms of susceptibility to spoof attacks, non-universality, large intra-user variations, and noise in sensed data. The Multimodal biometric systems defeat various limitations of unimodal biometric systems as the sources of different biometrics typically compensate for the inherent limitations of one another. The objective of this article is to analyze various methods of information fusion for biometrics, and summarize, to conclude with direction on future research proficiency in a multimodal biometric system using ECG, Fingerprint and Face features. This paper is furnished as a ready reckoner for those researchers, who wish to persue their work in the area of biometrics.
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Jovanovic, Bojan, Ivan Milenkovic, Marija Bogicevic-Sretenovic, and Dejan Simic. "Extending identity management system with multimodal biometric authentication." Computer Science and Information Systems 13, no. 2 (2016): 313–34. http://dx.doi.org/10.2298/csis141030003j.
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Techniques for authentication that are used in today's identity management systems are vulnerable when they are used over the network. In order to prevent fraud and unauthorized data access, it is important to ensure the identity of the person who submitted authentication credentials. The authentication process can be additionally secured by using biometric data for user verification. Moreover, precision of biometric authentication can be improved by the use of multimodal biometrics. This paper presents a system which has been designed for identity management based on FreeIPA solution for digital identity management and MMBio framework for multimodal biometrics. Proposed system provides multifactor authentication, where MMBio framework is used for handling user biometric data. Developed prototype confirms possible integration of identity management and multimodal biometric systems.
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Leghari, Mehwish, Shahzad Memon, Lachman Das Dhomeja, and Akhter Hussain Jalbani. "Analyzing the Effects of Data Augmentation on Single and Multimodal Biometrics." Mehran University Research Journal of Engineering and Technology 39, no. 3 (July 1, 2020): 647–56. http://dx.doi.org/10.22581/muet1982.2003.19.
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Now-a-days, in the field of machine learning the data augmentation techniques are common in use, especially with deep neural networks, where a large amount of data is required to train the network. The effectiveness of the data augmentation technique has been analyzed for many applications; however, it has not been analyzed separately for the multimodal biometrics. This research analyzes the effects of data augmentation on single biometric data and multimodal biometric data. In this research, the features from two biometric modalities: fingerprint and signature, have been fused together at the feature level. The primary motivation for fusing biometric data at feature level is to secure the privacy of the user’s biometric data. The results that have been achieved by using data augmentation are presented in this research. The experimental results for the fingerprint recognition, signature recognition and the feature-level fusion of fingerprint with signature have been presented separately. The results show that the accuracy of the training classifier can be enhanced with data augmentation techniques when the size of real data samples is insufficient. This research study explores that how the effectiveness of data augmentation gradually increases with the number of templates for the fused biometric data by making the number of templates double each time until the classifier achieved the accuracy of 99%.
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KOPCZEWSKI, Marian, and Tomasz SMAL. "POSSIBILITIES FOR THE USE OF BIOMETRIC DATA IN SECURITY SYSTEMS." Journal of Science of the Gen. Tadeusz Kosciuszko Military Academy of Land Forces 186, no. 4 (October 2, 2017): 168–79. http://dx.doi.org/10.5604/01.3001.0010.7226.
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Possibilities for the use of biometric data are growing and hence their practical application is also increasing. Therefore, an important element to be considered in the design, construction and exploitation of systems using biometrics is the question of identifying a specific person and assigning him or her to the relevant data contained in the documents or databases. The ability and, in some cases, the need to use biometric data results from the growing use of information technology in everyday life and the ever increasing attempts to steal the identity of those using these technologies. Modern IT systems often have a high level of security in terms of protection and access to data, and in particular the management of security systems. The article presents an outline of the theory related to the possibility of using and applying biometric data to provide security and have the ability to inspect officers of various departments. The subject of analysis also considered the possibility of using security measures in the form of biometric data identification for the purpose of securing the security services.
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KHUWAJA, GULZAR A., and A. N. ABU-REZQ. "DATA ACQUISITION AND RECOGNITION OF FINGERPRINTS WITH LVQ." International Journal of Computational Intelligence and Applications 03, no. 01 (March 2003): 65–88. http://dx.doi.org/10.1142/s1469026803000811.
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A typical biometric system has three distinct phases. These are biometric data acquisition, feature extraction, and decision-making. The first step, the acquisition phase, is extremely important. If high quality images are not obtained, the next phase cannot operate reliably. Fingerprint recognition remains as one of the most prominent biometric identification methods. In this paper, we develop a prototype optical-based fingerprints data acquisition system using a CCD digital still camera to capture a complete impression of finger area required for accurately identifying an individual and present an image-based approach for online fingerprint recognition with the objective to increase the overall matching performance. The fingerprint images are matched based on features extracted with an adaptive learning vector quantization (LVQ) neural network to yield peak recognition of 98.6% for a random set of 300 test prints (100 fingers × 3 images). This system can be adopted as a multi-modal biometrics where two or more fingers are matched.
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Ladhiya, Karan. "Privacy Preserving Bio-Metric Authentication." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 114–24. http://dx.doi.org/10.22214/ijraset.2022.40570.
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Abstract: Biometric authentication is now extensively used in several systems and applications to authenticate users using their biometrics. The biometrics of the users are compared to the biometric templates already stored on the server, and if there is a match, only the user is permitted to enter the system. However, because each user's biometrics are unique, it is more important than the user's actual biometric data is never leaked. Moreover, the utilization of the user's actual biometric data for comparisons during the authentication process can't be done because the revelation of the user's actual biometrics to the server should not be done. Throughout authentication, each user will encrypt his biometrics and then transmit this encrypted data to the server for comparison, and this data will never be decrypted for privacy reasons during the whole authentication process. To compare two encrypted data without decrypting them, the present study uses the homomorphic properties of the Pailler cryptosystem which will be the encryption of the algorithm for the comparison part. The use of Euclidean Distance is made to find the squared distance between the users’ queried feature vector and the templates stored into the server. In the end, among all the distances, the minimum distance will be chosen and will compare with some predefined threshold to decide whether the user is an authenticated user or not.
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Medjahed, Chahreddine, Abdellatif Rahmoun, Christophe Charrier, and Freha Mezzoudj. "A deep learning-based multimodal biometric system using score fusion." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (March 1, 2022): 65. http://dx.doi.org/10.11591/ijai.v11.i1.pp65-80.
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Recent trends in artificial intelligence tools-based biometrics have overwhelming attention to security matters. The hybrid approaches are motivated by the fact that they combine mutual strengths and they overcome their limitations. Such approaches are being applied to the fields of biomedical engineering. A biometric system uses behavioural or physiological characteristics to identify an individual. The fusion of two or more of these biometric unique characteristics contributes to improving the security and overcomes the drawbacks of unimodal biometric-based security systems. This work proposes efficent multimodal biometric systems based on matching score concatenation fusion of face, left and right palm prints. Multimodal biometric identification systems using convolutional neural networks (CNN) and k-nearest neighbors (KNN) are proposed and trained to recognize and identify individuals using multi-modal biometrics scores. Some popular biometrics benchmarks such as FEI face dataset and IITD palm print database are used as raw data to train the biometric systems to design a strong and secure verification/identification system. Experiments are performed on noisy datasets to evaluate the performance of the proposed model in extreme scenarios. Computer simulation results show that the CNN and KNN multi-modal biometric system outperforms most of the most popular up to date biometric verification techniques.
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NAZAR, AKIF, ISSA TRAORÉ, and AHMED AWAD E. AHMED. "INVERSE BIOMETRICS FOR MOUSE DYNAMICS." International Journal of Pattern Recognition and Artificial Intelligence 22, no. 03 (May 2008): 461–95. http://dx.doi.org/10.1142/s0218001408006363.
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Various techniques have been proposed in different literature to analyze biometric samples collected from individuals. However, not a lot of attention has been paid to the inverse problem, which consists of synthesizing artificial biometric samples that can be used for testing existing biometric systems or protecting them against forgeries. In this paper, we present a framework for mouse dynamics biometrics synthesis. Mouse dynamics biometric is a behavioral biometric technology, which allows user recognition based on the actions received from the mouse input device while interacting with a graphical user interface. The proposed inverse biometric model learns from random raw samples collected from real users and then creates synthetic mouse actions for fake users. The generated mouse actions have unique behavioral properties separate from the real mouse actions. This is shown through various comparisons of behavioral metrics as well as a Kolmogorov–Smirnov test. We also show through a two-fold cross-validation test that by submitting sample synthetic data to an existing mouse biometrics analysis model we achieve comparable performance results as when the model is applied to real mouse data.
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Paul, Padma P., and Marina L. Gavrilova. "A Novel Cross Folding Algorithm for Multimodal Cancelable Biometrics." International Journal of Software Science and Computational Intelligence 4, no. 3 (July 2012): 20–37. http://dx.doi.org/10.4018/jssci.2012070102.
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Multimodal biometric systems have emerged as highly successful new approach to combat problems of unimodal biometric system such as intraclass variability, interclass similarity, data quality, non-universality, and sensitivity to noise. However, one major issue pertinent to unimodal system remains, which has to do with actual biometric characteristics of users being permanent and their number being limited. Thus, if a user’s biometric is compromised, it might be impossible or highly difficult to replace it in a particular system. The concept of cancelable biometric or cancelability is to transform a biometric data or feature into a new one so that the stored biometric template can be easily changed in a biometric security system. In this paper, the authors present a novel solution for cancelable biometrics in a multimodal system. They develop a new cancelable biometric template generation algorithm using random projection and transformation-based feature extraction and selection. Performance of the proposed algorithm is validated on a virtual multi-modal face and ear database.
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Ivanov, Alexander, and Alexeiy Sulavko. "Draft of the Third National Standard of Russia for Fast Automatic Learning of Large Correlation Neural Networks on Small Training Samples of Biometric Data." Voprosy kiberbezopasnosti, no. 3(43) (2021): 84–93. http://dx.doi.org/10.21681/2311-3456-2021-3-84-93.
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The aim of the study is to show that a biometrics-to-access code converter based on large networks of correlation neurons makes it possible to obtain an even longer key at the output while ensuring the protection of biometric data from compromise. The research method is the use of large «wide» neural networks with automatic learning for the implementation of the biometric authentication procedure, ensuring the protection of biometric personal data from compromise. Results of the study - the first national standard GOST R 52633.5 for the automatic training of neuron networks was focused only on a physically secure, trusted computing environment. The protection of the parameters of the trained neural network converters biometrics-code using cryptographic methods led to the need to use short keys and passwords for biometric-cryptographic authentication. It is proposed to build special correlation neurons in the meta-space of Bayes-Minkowski features of a higher dimension. An experiment was carried out to verify the patterns of kkeystroke dynamics using a biometrics-to-code converter based on the data set of the AIConstructor project. In the meta-space of features, the probability of a verification error turned out to be less (EER = 0.0823) than in the original space of features (EER = 0.0864), while in the protected execution mode of the biometrics-to-code converter, the key length can be increased by more than 19 times. Experiments have shown that the transition to the mat space of BayesMinkowski features does not lead to the manifestation of the “curse of dimension” problem if some of the original features have a noticeable or strong mutual correlation. The problem of ensuring the confidentiality of the parameters of trained neural network containers, from which the neural network converter biometrics-code is formed, is relevant not only for biometric authentication tasks. It seems possible to develop a standard for protecting artificial intelligence based on automatically trained networks of Bayesian-Minkowski correlation neurons.
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Taha, Mohammed A., and Hanaa M. Ahmed. "A fuzzy vault development based on iris images." EUREKA: Physics and Engineering, no. 5 (September 13, 2021): 3–12. http://dx.doi.org/10.21303/2461-4262.2021.001997.
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Biometric systems gather information from the person's biometric attributes, used extensively to authorize the individuals. Due to the obvious convenience of using specific individual traits such as face, fingerprints, palm veins, and irises, biometric authentication is becoming more common. In particular, Iris systems are in high demand for high-assurance applications, because they contain a broad feature set and remain stable. Authentication methods based on iris biometrics are now commonly used in a variety of fields. This is due to the fact that iris biometric authentication is both safer and more comfortable than conventional passwords. Template Security is a major concern in biometric systems. The template security mechanism ensures reusable, permanent, and un-linkable models. The Fuzzy Vault strategy is one of the most popular security schemes for Template protection.
Fuzzy vault has demonstrated to be an effective protection method but lacks revocability and security attacks. This article introduced an improved fuzzy vault system. The improved fuzzy vault system was introduced, which uses more than one key to protect biometric data. Different keys make the search space more detailed. The additional key was used to encrypt vault data, which stopped the intruder from accessing the information on the person's biometry. The system was tested using CASIA.v1 and IITD.v1 datasets, and findings showed that the system ensures the protection and authentication of the iris templates without compromising performance. The proposed modification gave a 0.0 % False Accepted Rate (FAR) for both the dataset and False Rejected Rate (FRR), 0.14 % for CASIA v1 and 0.12 % for ITTD v1 False Rejected rate
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Musambo, Lubasi Kakwete, and Jackson Phiri. "A Framework for Civil Registration in Developing Countries Based on Biometrics and ISO Standards." International Journal of ICT Research in Africa and the Middle East 8, no. 2 (July 2019): 32–74. http://dx.doi.org/10.4018/ijictrame.2019070103.
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Most developing countries in Africa have civil registration processes with inherent challenges that inhibit their efficiency and accuracy. Attempts at modernization and improvement are on-going. In this article, a biometric framework that can be used to mitigate the challenges inherent in biometric data management for the civil registration system in Zambia is presented. The proposed framework presented is based on ISO models and adapted for most developing countries with low Information and Communication Technologies. A baseline study was undertaken to assess the understanding and appreciation of biometrics within the Zambian community and how this data might be stored or managed. A study of the Zambian civil registration business process has been undertaken and the authors propose an automated civil registration business process. Results obtained show that currently, Zambia does NOT have a biometric framework that supervises use of biometric data. The proposed model once adopted would form a secure framework for civil registration based on biometrics and ISO standards.
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Omar, Bayan. "Fusion Method with Mean-discrete Algorithm in Feature level for Identical twins Identification." UHD Journal of Science and Technology 4, no. 2 (December 27, 2020): 141. http://dx.doi.org/10.21928/uhdjst.v4n2y2020.pp141-150.
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The study on twins is an important form of study in the forensic and biometrics field as twins share similar genetic traits. A biometric is one of the common types of pattern recognition which acquires biometric data from a person. From these data, a feature is established and extracted where these features can be used to identify individual. Exiting works in biometric identification concentrate on unimodal biometric identification. The high similarity in a pair of twin’s biometric may lead to miss performance. Hence, due to their great accurateness, multimodal biometric systems have become more favored than unimodal biometric systems in identical twins identification. However, these systems are highly complex. We proposed Mean-Discrete feature based fusion algorithm for Kurdish handwriting and fingerprint for identical twins detection. Its viability and advantage over the unimodal biometric systems are highlighted. This paper employed 800 images from 50 pairs of identical twins from Kurdistan Region to carry out the experiment.
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Tranberg, Charlotte Bagger. "Biometric Data in Scandinavia." European Business Law Review 19, Issue 2 (April 1, 2008): 387–403. http://dx.doi.org/10.54648/eulr2008023.
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Zaborska, Sylwia. "Regulacje prawne w zakresie ochrony danych biometrycznych na podstawie RODO." Studia Iuridica Lublinensia 28, no. 2 (December 2, 2019): 97. http://dx.doi.org/10.17951/sil.2019.28.2.97-106.
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<p>The purpose of this article is to draw attention to the possibility of using new methods for the identification and verification of individuals, i.e. biometric techniques. Nowadays, the use of biometrics grows, which entails the adaptation of legal norms to current trends. The author points out the changes in the protection of biometric data in connection with the introduction of the GDPR, especially in the context of making biometric data as a special category.</p>
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Wang, Yazhou, Bing Li, Yan Zhang, Jiaxin Wu, and Qianya Ma. "A Secure Biometric Key Generation Mechanism via Deep Learning and Its Application." Applied Sciences 11, no. 18 (September 13, 2021): 8497. http://dx.doi.org/10.3390/app11188497.
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Biometric keys are widely used in the digital identity system due to the inherent uniqueness of biometrics. However, existing biometric key generation methods may expose biometric data, which will cause users’ biometric traits to be permanently unavailable in the secure authentication system. To enhance its security and privacy, we propose a secure biometric key generation method based on deep learning in this paper. Firstly, to prevent the information leakage of biometric data, we utilize random binary codes to represent biometric data and adopt a deep learning model to establish the relationship between biometric data and random binary code for each user. Secondly, to protect the privacy and guarantee the revocability of the biometric key, we add a random permutation operation to shuffle the elements of binary code and update a new biometric key. Thirdly, to further enhance the reliability and security of the biometric key, we construct a fuzzy commitment module to generate the helper data without revealing any biometric information during enrollment. Three benchmark datasets including ORL, Extended YaleB, and CMU-PIE are used for evaluation. The experiment results show our scheme achieves a genuine accept rate (GAR) higher than the state-of-the-art methods at a 1% false accept rate (FAR), and meanwhile satisfies the properties of revocability and randomness of biometric keys. The security analyses show that our model can effectively resist information leakage, cross-matching, and other attacks. Moreover, the proposed model is applied to a data encryption scenario in our local computer, which takes less than 0.5 s to complete the whole encryption and decryption at different key lengths.
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Chiou, Shin-Yan. "Secure Method for Biometric-Based Recognition with Integrated Cryptographic Functions." BioMed Research International 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/623815.
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Biometric systems refer to biometric technologies which can be used to achieve authentication. Unlike cryptography-based technologies, the ratio for certification in biometric systems needs not to achieve 100% accuracy. However, biometric data can only be directly compared through proximal access to the scanning device and cannot be combined with cryptographic techniques. Moreover, repeated use, improper storage, or transmission leaks may compromise security. Prior studies have attempted to combine cryptography and biometrics, but these methods require the synchronization of internal systems and are vulnerable to power analysis attacks, fault-based cryptanalysis, and replay attacks. This paper presents a new secure cryptographic authentication method using biometric features. The proposed system combines the advantages of biometric identification and cryptographic techniques. By adding a subsystem to existing biometric recognition systems, we can simultaneously achieve the security of cryptographic technology and the error tolerance of biometric recognition. This method can be used for biometric data encryption, signatures, and other types of cryptographic computation. The method offers a high degree of security with protection against power analysis attacks, fault-based cryptanalysis, and replay attacks. Moreover, it can be used to improve the confidentiality of biological data storage and biodata identification processes. Remote biometric authentication can also be safely applied.
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Huang, Quan. "Multimodal Biometrics Fusion Algorithm Using Deep Reinforcement Learning." Mathematical Problems in Engineering 2022 (March 24, 2022): 1–9. http://dx.doi.org/10.1155/2022/8544591.
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Multimodal biometrics fusion plays an important role in the field of biometrics. Therefore, this paper presents a multimodal biometrics fusion algorithm using deep reinforcement learning. In order to reduce the influence of user behavior, user’s personal characteristics, and environmental light on image data quality, data preprocessing is realized through data transformation and single-mode biometric image region segmentation. A two-dimensional Gobar filter was used to analyze the texture of local sub-blocks, qualitatively describe the similarity between the filter and the sub-blocks and extract the phase information and local amplitude information of multimodal biometrics features. Deep reinforcement learning was used to construct the classifier of different modal biometrics, and the weighted sum fusion of different modal biometrics was implemented by fractional information. The multimodal biometrics fusion algorithm was designed. The Casia-iris-interval-v4 and NFBS datasets were used to test the performance of the proposed algorithm. The results show that the fused image quality is better, the feature extraction accuracy is between 84% and 93%, the average accuracy of feature classification is 97%, the multimodal biometric classification time is only 110 ms, the multimodal biometric fusion time is only 550 ms, the effect is good, and the practicability is strong.
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Damaševičius, Robertas, Rytis Maskeliūnas, Egidijus Kazanavičius, and Marcin Woźniak. "Combining Cryptography with EEG Biometrics." Computational Intelligence and Neuroscience 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/1867548.
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Cryptographic frameworks depend on key sharing for ensuring security of data. While the keys in cryptographic frameworks must be correctly reproducible and not unequivocally connected to the identity of a user, in biometric frameworks this is different. Joining cryptography techniques with biometrics can solve these issues. We present a biometric authentication method based on the discrete logarithm problem and Bose-Chaudhuri-Hocquenghem (BCH) codes, perform its security analysis, and demonstrate its security characteristics. We evaluate a biometric cryptosystem using our own dataset of electroencephalography (EEG) data collected from 42 subjects. The experimental results show that the described biometric user authentication system is effective, achieving an Equal Error Rate (ERR) of 0.024.
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Madianou, Mirca. "The Biometric Assemblage: Surveillance, Experimentation, Profit, and the Measuring of Refugee Bodies." Television & New Media 20, no. 6 (July 2, 2019): 581–99. http://dx.doi.org/10.1177/1527476419857682.
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Biometric technologies are routinely used in the response to refugee crises with the United Nations High Commissioner for Refugees (UNHCR) aiming to have all refugee data from across the world in a central population registry by the end of 2019. The article analyzes biometrics, artificial intelligence (AI), and blockchain as part of a technological assemblage, which I term the biometric assemblage. The article identifies five intersecting logics that explain wider transformations within the humanitarian sector and in turn shape the biometric assemblage. The acceleration of the rate of biometric registrations in the humanitarian sector between 2002 and 2019 reveals serious concerns regarding bias, data safeguards, data-sharing practices with states and commercial companies, experimentation with untested technologies among vulnerable people, and, finally, ethics. Technological convergence amplifies risks associated with each constituent technology of the biometric assemblage. The article finally argues that the biometric assemblage accentuates asymmetries between refugees and humanitarian agencies and ultimately entrenches inequalities in a global context.
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Chai, Tong-Yuen, Bok-Min Goi, Yong-Haur Tay, and and Zhe Jin. "A New Design for Alignment-Free Chaffed Cancelable Iris Key Binding Scheme." Symmetry 11, no. 2 (February 1, 2019): 164. http://dx.doi.org/10.3390/sym11020164.
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Iris has been found to be unique and consistent over time despite its random nature. Unprotected biometric (iris) template raises concerns in security and privacy, as numerous large-scale iris recognition projects have been deployed worldwide—for instance, susceptibility to attacks, cumbersome renewability, and cross-matching. Template protection schemes from biometric cryptosystems and cancelable biometrics are expected to restore the confidence in biometrics regarding data privacy, given the great advancement in recent years. However, a majority of the biometric template protection schemes have uncertainties in guaranteeing criteria such as unlinkability, irreversibility, and revocability, while maintaining significant performance. Fuzzy commitment, a theoretically secure biometric key binding scheme, is vulnerable due to the inherent dependency of the biometric features and its reliance on error correction code (ECC). In this paper, an alignment-free and cancelable iris key binding scheme without ECC is proposed. The proposed system protects the binary biometric data, i.e., IrisCodes, from security and privacy attacks through a strong and size varying non-invertible cancelable transform. The proposed scheme provides flexibility in system storage and authentication speed via controllable hashed code length. We also proposed a fast key regeneration without either re-enrollment or constant storage of seeds. The experimental results and security analysis show the validity of the proposed scheme.
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Singh, Bhanu, and Nirvisha Singh. "MoLaBSS: Server-Specific Add-On Biometric Security Layer Model to Enhance the Usage of Biometrics." Information 11, no. 6 (June 8, 2020): 308. http://dx.doi.org/10.3390/info11060308.
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With high-paced growth in biometrics, and its easy availability to capture various biometric features, it is emerging as one of the most valuable technologies for multifactor authentication to verify a user’s identity, for data security. Organizations encourage their members to use biometrics, but they are hesitant to use them due to perceived security risks. Because of its low usage rate, many medium and small segment organizations find it unfeasible to deploy robust biometric systems. We propose a server-specific add-on biometric security layer model (MoLaBSS) to enhance confidence in the usage of biometrics. We tested this model via a biometric mobile app, and the survey showed a favorable response of 80%. The innovative mobile app was tested for its usability and got a score of more than 71%. For test tool reliability, we examined the equal error rate (EER) of the app and got a reasonably low score of 6%. The results show good potential of this framework to enhance users’ confidence level in the usage of biometrics. Higher usage rates may make deployment of biometrics more cost-effective for many organizations to decrease their information security risk.
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Barzut, Srđan, Milan Milosavljević, Saša Adamović, Muzafer Saračević, Nemanja Maček, and Milan Gnjatović. "A Novel Fingerprint Biometric Cryptosystem Based on Convolutional Neural Networks." Mathematics 9, no. 7 (March 28, 2021): 730. http://dx.doi.org/10.3390/math9070730.
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Modern access controls employ biometrics as a means of authentication to a great extent. For example, biometrics is used as an authentication mechanism implemented on commercial devices such as smartphones and laptops. This paper presents a fingerprint biometric cryptosystem based on the fuzzy commitment scheme and convolutional neural networks. One of its main contributions is a novel approach to automatic discretization of fingerprint texture descriptors, entirely based on a convolutional neural network, and designed to generate fixed-length templates. By converting templates into the binary domain, we developed the biometric cryptosystem that can be used in key-release systems or as a template protection mechanism in fingerprint matching biometric systems. The problem of biometric data variability is marginalized by applying the secure block-level Bose–Chaudhuri–Hocquenghem error correction codes, resistant to statistical-based attacks. The evaluation shows significant performance gains when compared to other texture-based fingerprint matching and biometric cryptosystems.
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Zaborska, Sylwia. "Wybrane aspekty prawne dotyczące przetwarzania danych biometrycznych pracowników." Studia Iuridica Lublinensia 30, no. 4 (October 13, 2021): 593. http://dx.doi.org/10.17951/sil.2021.30.4.593-603.
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<p>Given the growing popularity of biometrics, doubts about the conditions for biometric data processing can be noticed in practice. These inaccuracies take place in various areas of law, including labour law. This article provides a theoretical discussion on the processing of special categories of data. It aims to point to the need for appropriate legal regulations to ensure the security of the processing of biometric data of employees and candidate employees. The article starts with clarifying the concept of biometric data and discusses the practical aspects of the use of biometric tools. Further on, the author analyses the legal regulations concerning the processing of biometric data in the relations between the employer as the personal data controller and the employee as the data subject. As a result of the studies carried out, a position was presented which indicates that the employer who processes biometric data of employees and candidates for employment should always find out whether he has legal justification to process the data in question. This article is one of the few studies on the processing of biometric data in Polish literature on the subject. The main purpose hereof is to present situations under the current legislation, in which the employer can process biometric data of its employees. The article is a form of universal presentation of the problem and may be of interest especially to legal practitioners.</p>
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Bourcha, Crystalie, Maria Louiza Deftou, and AnthiKoskina no. "Data mining of biometric data: revisiting the concept of private life?" IUS ET SCIENTIA 3, no. 2 (2017): 37–62. http://dx.doi.org/10.12795/ietscientia.2017.i02.04.
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Arunarani, S., and R. Gobinath. "A survey on multimodal biometrics for human authentication." International Journal of Engineering & Technology 7, no. 3.3 (June 8, 2018): 273. http://dx.doi.org/10.14419/ijet.v7i2.33.14167.
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Authentication process identifies an individual to get an endorsed access by entering their login credentials. The inconvenience with this method is the user must remember the keywords, and the passwords can be predicted or if it is hard to guess it will be cracked through brute force. Due to this fault, this method is lack of integrity. Biometrics sample recognize a person based on his behavioral or physiological char-acteristics. Unimodal biometric systems have to resist with a different types of problems such as inconsistent data, intra-class variations, deceit attacks and high error rates. Multimodal biometrics implements secure authentication using various biometric traits. This survey gives us a wide scope for improving and enhancing the biometric applications. In this paper, we have explained multimodal biometrics to decrease the error rate and increase the security.
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Fianyi, Israel, and Tanveer Zia. "Biometric Technology Solutions to Countering Today's Terrorism." International Journal of Cyber Warfare and Terrorism 6, no. 4 (October 2016): 28–40. http://dx.doi.org/10.4018/ijcwt.2016100103.
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The purpose of this paper is to examine the relevance of biometric technologies in increasing the fight against terrorism and other related border security challenges such as identity dominance. Since the 11th September, 2001 catastrophe in USA the need for biometrics technology for identification purpose has become important. Consequently, the many ripostes that were renewed on identity management included enhanced use of biometrics to verify and authenticate travellers at various airports as well as the use of video surveillance equipped with facial recognition sensors. The growth in data and storage devices have also become a critical phenomenon in biometrics deployment, the swiftness and accuracy with which these biometrics details can be processed is a prevailing challenge. This paper provides an extensive review of literatures on prospects of biometric technologies and other interrelated technologies in the fight against terrorism. To date, there is relatively meagre academic research examining how biometric technologies enhance border security as well as individual security.
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Szűcs, Kata Rebeka, Arnold Őszi, and Tibor Kovács. "Mobile Biometrics and their Risks." Hadmérnök 15, no. 4 (2020): 15–28. http://dx.doi.org/10.32567/hm.2020.4.2.
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The present article aims to introduce the ways of secure access control, with a special emphasis on biometric solutions on mobile devices. Apart from secure biometric data storage, which is also a very important aspect of this topic, there are several other types of threats. On the following pages we provide a short description of the possible risks of biometric systems. In order to understand the current status and attitude towards biometrics, we introduce our own survey as well.
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Pathak, Mrunal. "Multimodal Biometric Authentication for Smartphones." International Journal for Research in Applied Science and Engineering Technology 9, no. 12 (December 31, 2021): 1559–68. http://dx.doi.org/10.22214/ijraset.2021.39569.
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Abstract: Smartphones have become a crucial way of storing sensitive information; therefore, the user's privacy needs to be highly secured. This can be accomplished by employing the most reliable and accurate biometric identification system available currently which is, Eye recognition. However, the unimodal eye biometric system is not able to qualify the level of acceptability, speed, and reliability needed. There are other limitations such as constrained authentication in real time applications due to noise in sensed data, spoof attacks, data quality, lack of distinctiveness, restricted amount of freedom, lack of universality and other factors. Therefore, multimodal biometric systems have come into existence in order to increase security as well as to achieve better performance.[1] This paper provides an overview of different multimodal biometric (multibiometric) systems for smartphones being employed till now and also proposes a multimodal biometric system which can possibly overcome the limitations of the current biometric systems. Keywords: Biometrics, Unimodal, Multimodal, Fusion, Multibiometric Systems
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Channegowda, Arjun Benagatte, and H. N. Prakash. "Multimodal biometrics of fingerprint and signature recognition using multi-level feature fusion and deep learning techniques." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (April 1, 2021): 187. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp187-195.
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Providing security in biometrics is the major challenging task in the current situation. A lot of research work is going on in this area. Security can be more tightened by using complex security systems, like by using more than one biometric trait for recognition. In this paper multimodal biometric models are developed to improve the recognition rate of a person. The combination of physiological and behavioral biometrics characteristics is used in this work. Fingerprint and signature biometrics characteristics are used to develop a multimodal recognition system. Histograms of oriented gradients (HOG) features are extracted from biometric traits and for these feature fusions are applied at two levels. Features of fingerprint and signatures are fused using concatenation, sum, max, min, and product rule at multilevel stages, these features are used to train deep learning neural network model. In the proposed work, multi-level feature fusion for multimodal biometrics with a deep learning classifier is used and results are analyzed by a varying number of hidden neurons and hidden layers. Experiments are carried out on SDUMLA-HMT, machine learning and data mining lab, Shandong University fingerprint datasets, and MCYT signature biometric recognition group datasets, and encouraging results were obtained.
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Farmanullah Jan, Farmanullah Jan, Imran Usman Imran Usman, and Shahid A. Khan Shahid A. Khan. "Robust iris biometric system for visible wavelength data." Chinese Optics Letters 11, no. 8 (2013): 081501–81507. http://dx.doi.org/10.3788/col201311.081501.
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Kulikov, A. A. "Application of biometric systems in face identification technologies." Russian Technological Journal 9, no. 3 (June 28, 2021): 7–14. http://dx.doi.org/10.32362/2500-316x-2021-9-3-7-14.
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The paper presents an analytical review of the application of biometric recognition systems in relation to facial image identification technologies. The classification of biometric systems is presented. The trends of technological progress in the field of biometrics and facial recognition capabilities are considered. It is determined that in 2020 there is a trend of transition from the use of biometric recognition technologies in traditional state security systems to the sphere of commercial and user applications. The process of «linking» encryption keys and passwords with the biometric parameters of the data subject is described. It is proposed that a biometric feature and a biometrics parameter mean a certain value that has a physical meaning that characterizes the subject itself. The possibility of using circular neighborhood and bilinear interpolation of pixel intensity values in biometrics is also presented. This will make it possible to build a local binary template. In order to solve the problem of identification of persons, it is advisable to investigate the essence of biometric systems in the technologies of identification of persons, their types, identifying the shortcomings of each of them, on the basis of which to present the directions of elimination and search for the most reliable technologies. The essence of the use of biometric systems in the technologies of identification of persons is, for example, that the user can provide the bank or other counterparty with evidence that it is he who wants to use the services on his accounts. At the same time, the demand has increased for contactless biometric solutions. These technologies are implemented in order to conduct additional biometric verification of users. This allows to minimize possible fraud or violation of the internal rules of the service, for example, the transfer of accounts of some registered users to others.
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McAteer, Ian, Ahmed Ibrahim, Guanglou Zheng, Wencheng Yang, and Craig Valli. "Integration of Biometrics and Steganography: A Comprehensive Review." Technologies 7, no. 2 (April 8, 2019): 34. http://dx.doi.org/10.3390/technologies7020034.
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The use of an individual’s biometric characteristics to advance authentication and verification technology beyond the current dependence on passwords has been the subject of extensive research for some time. Since such physical characteristics cannot be hidden from the public eye, the security of digitised biometric data becomes paramount to avoid the risk of substitution or replay attacks. Biometric systems have readily embraced cryptography to encrypt the data extracted from the scanning of anatomical features. Significant amounts of research have also gone into the integration of biometrics with steganography to add a layer to the defence-in-depth security model, and this has the potential to augment both access control parameters and the secure transmission of sensitive biometric data. However, despite these efforts, the amalgamation of biometric and steganographic methods has failed to transition from the research lab into real-world applications. In light of this review of both academic and industry literature, we suggest that future research should focus on identifying an acceptable level steganographic embedding for biometric applications, securing exchange of steganography keys, identifying and address legal implications, and developing industry standards.
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Tot, Ivan, Jovan Bajčetić, Boriša Jovanović, Mladen Trikoš, Dušan Bogićević, and Tamara Gajić. "Biometric standards and methods." Vojnotehnicki glasnik 69, no. 4 (2021): 963–77. http://dx.doi.org/10.5937/vojtehg69-32296.
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Introduction/purpose: Nowadays, user identification systems play a very important role in modern society. Complex security requirements have led experts to explore ways in which biometric data can be used to identify user identities. This paper presents an overview of biometric standards and methods which can be used to identify users in biometric systems, and therefore to protect information and communication systems. Methods: This paper deals with the problem of standardization in the field of biometrics. The first part of the paper presents concrete examples of the most widely used biometric standards. The second part of the paper gives an overview of the most used biometric methods. Results: The obtained results show that the development of biometric systems and biometric sensors contributes to better protection of identity from misuse, because biometric technologies have great potential for improving the security and accuracy of system operation. Biometric systems improve the security of users and also provide much greater precision in establishing identity. Conclusion: The development of biometric standards should focus on their interconnectivity, as well as on increasing connectivity with other IT standards.
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Griniuk, Marija. "Performance Art Using Biometric Data." Art History & Criticism 17, no. 1 (November 15, 2021): 101–12. http://dx.doi.org/10.2478/mik-2021-0009.
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Summary This research analyzes performance art that uses biometric data, based on two concept perspectives – inhuman interconnections and transcorporeality – applied to examples of European performance art from Lithuania, Finland, Poland, and Denmark. The term performance art theoretically refers to all art that involves the human body, human biometric data, inhuman interconnections, transcorporeality, and liminal space. This study examines the differences between wide-scope interactive art and design and performance art involving biometric data created through the application of recent developments in consumer technology for live events. This research examined three case projects through the method of autoethnography. The data presented in the article was either collected during the author’s performance art events or at performances the author was attending as a visitor. The cases are analyzed by means of qualitative data analysis, utilizing terms representing human biometric data and interactivity adopted from research within the fields of interactive art and interactive design. The study examines the combination of biometric data and art to explain the phenomenon of humans meeting technology, revealed through data collected from a body and transmitted to an audience during a performance art event. The conclusion revisits the key terms – performance art, biometric data, inhuman interconnections and transcorporeality – as applied to artistic practices, where performance art and biometric data meet.
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Seo, Minhye, Jong Hwan Park, Youngsam Kim, Sangrae Cho, Dong Hoon Lee, and Jung Yeon Hwang. "Construction of a New Biometric-Based Key Derivation Function and Its Application." Security and Communication Networks 2018 (December 2, 2018): 1–14. http://dx.doi.org/10.1155/2018/6107912.
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Biometric data is user-identifiable and therefore methods to use biometrics for authentication have been widely researched. Biometric cryptosystems allow for a user to derive a cryptographic key from noisy biometric data and perform a cryptographic task for authentication or encryption. The fuzzy extractor is known as a prominent biometric cryptosystem. However, the fuzzy extractor has a drawback in that a user is required to store user-specific helper data or receive it online from the server with additional trusted channel, to derive a correct key. In this paper, we present a new biometric-based key derivation function (BB-KDF) to address the issues. In our BB-KDF, users are able to derive cryptographic keys solely from their own biometric data: users do not need any other user-specific helper information. We introduce a security model for the BB-KDF. We then construct the BB-KDF and prove its security in our security model. We then propose an authentication protocol based on the BB-KDF. Finally, we give experimental results to analyze the performance of the BB-KDF. We show that our proposed BB-KDF is computationally efficient and can be deployed on many different kinds of devices.
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Nita, Stefania, Marius Mihailescu, and Valentin Pau. "Security and Cryptographic Challenges for Authentication Based on Biometrics Data." Cryptography 2, no. 4 (December 6, 2018): 39. http://dx.doi.org/10.3390/cryptography2040039.
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Authentication systems based on biometrics characteristics and data represents one of the most important trend in the evolution of the society, e.g., Smart City, Internet-of-Things (IoT), Cloud Computing, Big Data. In the near future, biometrics systems will be everywhere in the society, such as government, education, smart cities, banks etc. Due to its uniqueness, characteristic, biometrics systems will become more and more vulnerable, privacy being one of the most important challenges. The classic cryptographic primitives are not sufficient to assure a strong level of secureness for privacy. The current paper has several objectives. The main objective consists in creating a framework based on cryptographic modules which can be applied in systems with biometric authentication methods. The technologies used in creating the framework are: C#, Java, C++, Python, and Haskell. The wide range of technologies for developing the algorithms give the readers the possibility and not only, to choose the proper modules for their own research or business direction. The cryptographic modules contain algorithms based on machine learning and modern cryptographic algorithms: AES (Advanced Encryption System), SHA-256, RC4, RC5, RC6, MARS, BLOWFISH, TWOFISH, THREEFISH, RSA (Rivest-Shamir-Adleman), Elliptic Curve, and Diffie Hellman. As methods for implementing with success the cryptographic modules, we will propose a methodology which can be used as a how-to guide. The article will focus only on the first category, machine learning, and data clustering, algorithms with applicability in the cloud computing environment. For tests we have used a virtual machine (Virtual Box) with Apache Hadoop and a Biometric Analysis Tool. The weakness of the algorithms and methods implemented within the framework will be evaluated and presented in order for the reader to acknowledge the latest status of the security analysis and the vulnerabilities founded in the mentioned algorithms. Another important result of the authors consists in creating a scheme for biometric enrollment (in Results). The purpose of the scheme is to give a big overview on how to use it, step by step, in real life, and how to use the algorithms. In the end, as a conclusion, the current work paper gives a comprehensive background on the most important and challenging aspects on how to design and implement an authentication system based on biometrics characteristics.
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Alam, Varisha. "Ordering of Huge Biometric Information in Database System." Journal of Informatics Electrical and Electronics Engineering (JIEEE) 2, no. 2 (June 6, 2021): 1–19. http://dx.doi.org/10.54060/jieee/002.02.011.
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The word biometrics is derived from the Greek words 'bios' and 'metric' which means living and calculation appropriately. Biometrics is the electronic identification of individuals based on their physiological and biological features. Biometric attributes are data take out from biometric test which can be used for contrast with a biometric testimonial. Biometrics composed methods for incomparable concede humans based upon one or more inherent material or behavioral characteristics. In Computer Science, bio-metrics is employed as a kind of recognition access management and access command. Biometrics has quickly seemed like an auspicious technology for attestation and has already found a place in the most sophisticated security areas. A systematic clustering technique has been there for partitioning huge biometric databases throughout recognition. As we tend to are still obtaining the higher bin-miss rate, so this work is predicated on conceiving an ordering strategy for recognition of huge biometric database and with larger precision. This technique is based on the modified B+ tree that decreases the disk accesses. It reduced the information retrieval time and feasible error rates. The ordering technique is employed to proclaims a person’s identity with a reduced rate of differentiation instead of searching the whole database. The response time degenerates, further-more because the accuracy of the system deteriorates as the size of the database increases. Hence, for vast applications, the requirement to reduce the database to a little fragment seems to attain higher speeds and improved accuracy.