Pattern mining approaches used in sensor-based biometric recognition: a review

Sensing technologies place significant interest in the use of biometrics for the recognition and assessment of individuals. Pattern mining techniques have established a critical step in the progress of sensor-based biometric systems that are capable of perceiving, recognizing and computing sensor data, being a technology that searches for the high-level information about pattern recognition from low-level sensor readings in order to construct an artificial substitute for human recognition. The design of a successful sensor-based biometric recognition system needs to pay attention to the different issues involved in processing variable data being - acquisition of biometric data from a sensor, data pre-processing, feature extraction, recognition and/or classification, clustering and validation. A significant number of approaches from image processing, pattern identification and machine learning have been used to process sensor data. This paper aims to deliver a state-of-the-art summary and present strategies for utilizing the broadly utilized pattern mining methods in order to identify the challenges as well as future research directions of sensor-based biometric systems

Biometrics for internet‐of‐things security: A review

The large number of Internet‐of‐Things (IoT) devices that need interaction between smart devices and consumers makes security critical to an IoT environment. Biometrics offers an interesting window of opportunity to improve the usability and security of IoT and can play a significant role in securing a wide range of emerging IoT devices to address security challenges. The purpose of this review is to provide a comprehensive survey on the current biometrics research in IoT security, especially focusing on two important aspects, authentication and encryption. Regarding authentication, contemporary biometric‐based authentication systems for IoT are discussed and classified based on different biometric traits and the number of biometric traits employed in the system. As for encryption, biometric‐cryptographic systems, which integrate biometrics with cryptography and take advantage of both to provide enhanced security for IoT, are thoroughly reviewed and discussed. Moreover, challenges arising from applying biometrics to IoT and potential solutions are identified and analyzed. With an insight into the state‐of‐the‐art research in biometrics for IoT security, this review paper helps advance the study in the field and assists researchers in gaining a good understanding of forward‐looking issues and future research directions

Multibiometric security in wireless communication systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 05/08/2010.This thesis has aimed to explore an application of Multibiometrics to secured wireless communications. The medium of study for this purpose included Wi-Fi, 3G, and WiMAX, over which simulations and experimental studies were carried out to assess the performance. In specific, restriction of access to authorized users only is provided by a technique referred to hereafter as multibiometric cryptosystem. In brief, the system is built upon a complete challenge/response methodology in order to obtain a high level of security on the basis of user identification by fingerprint and further confirmation by verification of the user through text-dependent speaker recognition. First is the enrolment phase by which the database of watermarked fingerprints with memorable texts along with the voice features, based on the same texts, is created by sending them to the server through wireless channel. Later is the verification stage at which claimed users, ones who claim are genuine, are verified against the database, and it consists of five steps. Initially faced by the identification level, one is asked to first present one’s fingerprint and a memorable word, former is watermarked into latter, in order for system to authenticate the fingerprint and verify the validity of it by retrieving the challenge for accepted user. The following three steps then involve speaker recognition including the user responding to the challenge by text-dependent voice, server authenticating the response, and finally server accepting/rejecting the user. In order to implement fingerprint watermarking, i.e. incorporating the memorable word as a watermark message into the fingerprint image, an algorithm of five steps has been developed. The first three novel steps having to do with the fingerprint image enhancement (CLAHE with 'Clip Limit', standard deviation analysis and sliding neighborhood) have been followed with further two steps for embedding, and extracting the watermark into the enhanced fingerprint image utilising Discrete Wavelet Transform (DWT). In the speaker recognition stage, the limitations of this technique in wireless communication have been addressed by sending voice feature (cepstral coefficients) instead of raw sample. This scheme is to reap the advantages of reducing the transmission time and dependency of the data on communication channel, together with no loss of packet. Finally, the obtained results have verified the claims

Integration of biometrics and steganography: A comprehensive review

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

ADAPTABLE FINGERPRINT MINUTIAE EXTRACTION ALGORITHM BASED-ON CROSSING NUMBER METHOD FOR HARDWARE IMPLEMENTATION USING FPGA DEVICE

In this article. a main perspective of developing and implementing fingerprint extraction and matching algorithms as a pari of fingerprint recognition system is focused. First, developing a simple algorithm to extract fingerprint features and test this algorithm on Pc. The second thing is implementing this algorithm into FPGA devices. The major research topics on which the proposed approach is developing and modifying fingerprint extraction feature algorithm. This development and modification are using crossing number method on pixel representation value '0'. In this new proposed algorithm, it is no need a process concerning ROI segmentation and no trigonometry calculation. And specially in obtaining their parameters using Angle Calculation Block avoiding floating points calculation. As this method is local feature that usually involve with 60-100 minutiae points, makes the template is small in size. Providing FAR. FRR and EER, performs the performance evaluation of proposed algorithm. The result is an adaptable fingerprint minutiae extraction algorithm into hardware implementation with 14.05 % of EEl?, better than reference algorithm, which is 20.39 % . The computational time is 18 seconds less than a similar method, which takes 60-90 seconds just for pre-processing step. The first step of algorithm implementation in hardware environment (embedded) using FPGA Device by developing IP Core without using any soft processor is presented

Recent Application in Biometrics

In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers

A practical application of a text-independent speaker authentication system on mobile devices

The growing market of mobile devices forces to question about how to protect users’ credentials and data stored on such devices. Authentication mechanisms remain the first layer of security in the use of mobile devices. However, several of such mechanisms that have been already proposed were designed in a machine point of view. As a matter of fact, they are not compatible with behaviors human have while using their mobile devices in the daily life. Consequently, users adopted unsafe habits that may compromise the proper functioning of authentication mechanisms according to the safety aspect. The first main objective of this research project is to highlight strengths and weaknesses of current authentication systems, from the simpler ones such as PIN (Personal Identification Number) to the more complex biometric systems such as fingerprint. Then, this thesis offers an exhaustive evaluation of existing schemes. For this evaluation, we rely on some existing criteria and we also propose some new ones. Suggested criteria are chiefly centered on the usability of these authentica-tion systems. Secondly, this thesis presents a practical implementation of a text-independent speaker au-thentication system for mobile devices. We place a special attention in the choice of algorithms with low-computational costs since we want that the system operates without any network communication. Indeed, the enrollment, as well as the identification process are achieved onto the device itself. To this end, our choice was based on the extraction of Linear Prediction Cepstral Coefficients (LPCCs) (Furui 1981; O'Shaughnessy 1988) to obtain relevant voice features and the Naïve Bayes classifier (Zhang 2004) to predict at which speaker a given utterance corresponds. Furthermore, the authenti-cation decision was enhanced in order to overcome misidentification. In that sense, we introduced the notion of access privileges (i.e. public, protected, private) that the user has to attribute to each appli-cation installed on his/her mobile device. Then, the safest authority is granted through the result of the speaker identification decision as well as the analysis of the user’s location and the presence of a headset. In order to evaluate the proposed authentication system, eleven participants were involved in the experiment, which was conducted in two different environments (i.e. quiet and noisy). Moreover, we also employed public speech corpuses to compare this implementation to existing methods. Results obtained have shown that our system is a relevant, accurate and efficient solution to authenticate users on their mobile devices. Considering acceptability issues which were pointed out by some users, we suggest that the proposed authentication system should be either employed as part of a multilayer authentication, or as a fallback mechanism, to cover most of the user needs and usages. La croissance du marché des dispositifs mobiles implique de se questionner au sujet de comment protéger l’identité ainsi que les données personnelles des utilisateurs qui sont stockées sur ces appareils. En ce sens, les mécanismes d’authentification demeurent la première couche de sécurité dans l’utilisation des mobiles. Cependant, il apparaît que la plupart des mécanismes d’authentification qui ont été proposés, ont été conçus suivant un point de vue orienté machine plutôt qu’humain. En effet, ceux-ci ne s’adaptent généralement pas avec l’usage quotidien qu’ont les utilisateurs lorsqu’ils se servent leur téléphone. En conséquence, ils ont adopté des habitudes dangereuses qui peuvent compromettre le bon fonctionnement des systèmes d’authentification. Celles-ci peuvent alors remettre en question la sécurité de leur identité ainsi que la confidentialité de leur contenu numérique. Le premier objectif principal de ce projet de recherche est de faire ressortir les forces et les faiblesses des méthodes d’authentification qui existent actuellement, des plus simples comme le NIP (Numéro d’Identification Personnel) aux solutions biométriques plus complexes comme l’empreinte digitale. Par la suite, ce mémoire offre une évaluation exhaustive de ces solutions, basée sur des critères existant ainsi que de nouveaux critères que nous suggérons. Ces derniers sont majoritairement centrés sur l’utilisabilité des mécanismes d’authentification qui ont été examinés. Dans un second temps, ce mémoire présente une implémentation pratique, pour périphériques mobiles, d’un système d’authentification d’orateur indépendant de ce qui est prononcé par l’utilisateur. Pour concevoir un tel système, nous avons porté une attention particulière dans le choix d’algorithmes admettant un faible temps d’exécution afin de se prémunir des communications réseau. En effet, ceci nous permet alors de réaliser le processus d’entraînement ainsi que la reconnaissance, directement sur le mobile. Les choix technologiques se sont arrêtés sur l’extraction de coefficients spectraux (Linear Prediction Cepstral Coefficients) (Furui 1981; O'Shaughnessy 1988) afin d’obtenir des caractéristiques vocales pertinentes, ainsi que sur une classification naïve bayésienne (Zhang 2004) pour prédire à quel utilisateur correspond un énoncé donné. La décision finale, quant à elle, a été améliorée afin de se prémunir des mauvaises identifications. En ce sens, nous avons introduit la notion de droits d’accès spécifiques (i.e. publique, protégé ou privé) que l’utilisateur doit attribuer à chacune des applications installées sur son mobile. Ensuite, l’autorisation d’accès la plus adaptée est accordée, grâce au résultat retournée par l’identification de l’orateur, ainsi que par l’analyse de la localisation de l’utilisateur et de l’emploi d’un micro-casque. Pour réaliser l’évaluation du système que nous proposons ici, onze participants ont été recrutés pour la phase d’expérimentation. Cette dernière a été menée dans deux types d’environnements différents (i.e. silencieux et bruyant). De plus, nous avons aussi exploité des corpus de voix publiques afin de comparer notre implémentation à celles qui ont été proposées par le passé. Par conséquent, les résultats que nous avons obtenus ont montré que notre système constitue une solution pertinente, précise et efficace pour authentifier les utilisateurs sur leurs périphériques mobiles. Compte tenu des problèmes d’acceptabilité qui ont été mis en avant par certains testeurs, nous suggérons qu’un tel système puisse être utilisé comme faisant part d’une authentification à plusieurs facteurs, mais aussi comme une solution de repli, en cas d’échec du mécanisme principal, afin de couvrir la majorité des besoins et des usages des utilisateurs