The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Arun Ross - One of the best experts on this subject based on the ideXlab platform.
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what else does your Biometric Data reveal a survey on soft Biometrics
IEEE Transactions on Information Forensics and Security, 2016Co-Authors: Antitza Dantcheva, Petros Elia, Arun RossAbstract:Recent research has explored the possibility of extracting ancillary information from primary Biometric traits viz., face, fingerprints, hand geometry, and iris. This ancillary information includes personal attributes, such as gender, age, ethnicity, hair color, height, weight, and so on. Such attributes are known as soft Biometrics and have applications in surveillance and indexing Biometric Databases. These attributes can be used in a fusion framework to improve the matching accuracy of a primary Biometric system (e.g., fusing face with gender information), or can be used to generate qualitative descriptions of an individual (e.g., young Asian female with dark eyes and brown hair). The latter is particularly useful in bridging the semantic gap between human and machine descriptions of the Biometric Data. In this paper, we provide an overview of soft Biometrics and discuss some of the techniques that have been proposed to extract them from the image and the video Data. We also introduce a taxonomy for organizing and classifying soft Biometric attributes, and enumerate the strengths and limitations of these attributes in the context of an operational Biometric system. Finally, we discuss open research problems in this field. This survey is intended for researchers and practitioners in the field of Biometrics.
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Biometric template selection and update a case study in fingerprints
Pattern Recognition, 2004Co-Authors: Umut Uludag, Arun Ross, Anil K. JainAbstract:A Biometric authentication system operates by acquiring Biometric Data from a user and comparing it against the template Data stored in a Database in order to identify a person or to verify a claimed identity. Most systems store multiple templates per user in order to account for variations observed in a person's Biometric Data. In this paper we propose two methods to perform automatic template selection where the goal is to select prototype fingerprint templates for a finger from a given set of fingerprint impressions. The first method, called DEND, employs a clustering strategy to choose a template set that best represents the intra-class variations, while the second method, called MDIST, selects templates that exhibit maximum similarity with the rest of the impressions. Matching results on a Database of 50 different fingers, with 200 impressions per finger, indicate that a systematic template selection procedure as presented here results in better performance than random template selection. The proposed methods have also been utilized to perform automatic template update. Experimental results underscore the importance of these techniques.
Yi Hui Lin - One of the best experts on this subject based on the ideXlab platform.
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Provably Secure Remote Truly Three-Factor Authentication Scheme With Privacy Protection on Biometrics
IEEE Transactions on Information Forensics and Security, 2009Co-Authors: Chun-i Fan, Yi Hui LinAbstract:A three-factor authentication scheme combines Biometrics with passwords and smart cards to provide high-security remote authentication. Most existing schemes, however, rely on smart cards to verify Biometric characteristics. The advantage of this approach is that the user's Biometric Data is not shared with remote server. But the disadvantage is that the remote server must trust the smart card to perform proper authentication which leads to various vulnerabilities. To achieve truly secure three-factor authentication, a method must keep the user's Biometrics secret while still allowing the server to perform its own authentication. Our method achieves this. The proposed scheme fully preserves the privacy of the Biometric Data of every user, that is, the scheme does not reveal the Biometric Data to anyone else, including the remote servers. We demonstrate the completeness of the proposed scheme through the GNY (Gong, Needham, and Yahalom) logic. Furthermore, the security of our proposed scheme is proven through Bellare and Rogaway's model. As a further benefit, we point out that our method reduces the computation cost for the smart card.
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remote password authentication scheme with smart cards and Biometrics 12
Global Communications Conference, 2006Co-Authors: Chun-i Fan, Yi Hui Lin, Ruei-hau HsuAbstract:More and more researchers combine Biometrics with passwords and smart cards to design remote authentication schemes for the purpose of high-degree security. However, in most of these authentication schemes proposed in the literature so far, Biometric characteristics are verified in the smart cards only, not in the remote servers, during the authentication processes. Although this kind of design can prevent the Biometric Data of the users from being known to the servers, it will result in that they are not real three-factor authentication schemes and therefore some security flaws may occur since the remote servers do not indeed verify the security factor of Biometrics. In this paper we propose a truly three-factor remote authentication scheme where all of the three security factors, passwords, smart cards, and Biometric Data, are examined in the remote servers. Especially, the proposed scheme fully preserves the privacy of the Biometric Data of every user, that is, the scheme does not reveal the Biometric Data to anyone else, including the remote servers. Furthermore, we also demonstrate that the proposed scheme is immune to both the replay attacks and the offline-dictionary attacks and it satisfies the requirement of low-computation cost for smart-card users.
John Yearwood - One of the best experts on this subject based on the ideXlab platform.
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Protection of Privacy in Biometric Data
IEEE Access, 2016Co-Authors: Iynkaran Natgunanathan, Gleb Beliakov, Abid Mehmood, Y Xiang, John YearwoodAbstract:Biometrics is commonly used in many automated verification systems offering several advantages over traditional verification methods. Since Biometric features are associated with individuals, their leakage will violate individuals’ privacy, which can cause serious and continued problems as the Biometric Data from a person are irreplaceable. To protect the Biometric Data containing privacy information, a number of privacy-preserving Biometric schemes (PPBSs) have been developed over the last decade, but they have various drawbacks. The aim of this paper is to provide a comprehensive overview of the existing PPBSs and give guidance for future privacy-preserving Biometric research. In particular, we explain the functional mechanisms of popular PPBSs and present the state-of-the-art privacy-preserving Biometric methods based on these mechanisms. Furthermore, we discuss the drawbacks of the existing PPBSs and point out the challenges and future research directions in PPBSs.
Riccardo Lazzeretti - One of the best experts on this subject based on the ideXlab platform.
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privacy protection in Biometric based recognition systems a marriage between cryptography and signal processing
IEEE Signal Processing Magazine, 2015Co-Authors: Mauro Barni, Giulia Droandi, Riccardo LazzerettiAbstract:Systems employing Biometric traits for people authentication and identification are witnessing growing popularity due to the unique and indissoluble link between any individual and his/her Biometric characters. For this reason, Biometric templates are increasingly used for border monitoring, access control, membership verification, and so on. When employed to replace passwords, Biometrics have the added advantage that they do not need to be memorized and are relatively hard to steal. Nonetheless, unlike conventional security mechanisms such as passwords, Biometric Data are inherent parts of a person?s body and cannot be replaced if they are compromised. Even worse, compromised Biometric Data can be used to have access to sensitive information and to impersonate the victim for malicious purposes. For the same reason, Biometric leakage in a given system can seriously jeopardize the security of other systems based on the same Biometrics. A further problem associated with the use of Biometric traits is that, due to their uniqueness, the privacy of their owner is put at risk. Geographical position, movements, habits, and even personal beliefs can be tracked by observing when and where the Biometric traits of an individual are used to identify him/her.
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A privacy-compliant fingerprint recognition system based on homomorphic encryption and fingercode templates
IEEE 4th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010, 2010Co-Authors: Mauro Barni, Mario Di Di Raimondo, Dario Catalano, Pierluigi Failla, Tiziano Bianchi, Alessandro Piva, Ruggero Donida Labati, Vincenzo Piuri, Riccardo Lazzeretti, Fabio ScottiAbstract:The privacy protection of the Biometric Data is an important research topic, especially in the case of distributed Biometric systems. In this scenario, it is very important to guarantee that Biometric Data cannot be steeled by anyone, and that the Biometric clients are unable to gather any information different from the single user verification/identification. In a biométrie system with high level of privacy compliance, also the server that processes the biométrie matching should not learn anything on the Database and it should be impossible for the server to exploit the resulting matching values in order to extract any knowledge about the user presence or behavior. Within this conceptual framework, in this paper we propose a novel complete demonstrator based on a distributed biométrie system that is capable to protect the privacy of the individuals by exploiting cryptosystems. The implemented system computes the matching task in the encrypted domain by exploiting homomorphic encryption and using Fingercode templates. The paper describes the design methodology of the demonstrator and the obtained results. The demonstrator has been fully implemented and tested in real applicative conditions. Experimental results show that this method is feasible in the cases where the privacy of the Data is more important than the accuracy of the system and the obtained computational time is satisfactory.
Mauro Barni - One of the best experts on this subject based on the ideXlab platform.
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privacy protection in Biometric based recognition systems a marriage between cryptography and signal processing
IEEE Signal Processing Magazine, 2015Co-Authors: Mauro Barni, Giulia Droandi, Riccardo LazzerettiAbstract:Systems employing Biometric traits for people authentication and identification are witnessing growing popularity due to the unique and indissoluble link between any individual and his/her Biometric characters. For this reason, Biometric templates are increasingly used for border monitoring, access control, membership verification, and so on. When employed to replace passwords, Biometrics have the added advantage that they do not need to be memorized and are relatively hard to steal. Nonetheless, unlike conventional security mechanisms such as passwords, Biometric Data are inherent parts of a person?s body and cannot be replaced if they are compromised. Even worse, compromised Biometric Data can be used to have access to sensitive information and to impersonate the victim for malicious purposes. For the same reason, Biometric leakage in a given system can seriously jeopardize the security of other systems based on the same Biometrics. A further problem associated with the use of Biometric traits is that, due to their uniqueness, the privacy of their owner is put at risk. Geographical position, movements, habits, and even personal beliefs can be tracked by observing when and where the Biometric traits of an individual are used to identify him/her.
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A privacy-compliant fingerprint recognition system based on homomorphic encryption and fingercode templates
IEEE 4th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2010, 2010Co-Authors: Mauro Barni, Mario Di Di Raimondo, Dario Catalano, Pierluigi Failla, Tiziano Bianchi, Alessandro Piva, Ruggero Donida Labati, Vincenzo Piuri, Riccardo Lazzeretti, Fabio ScottiAbstract:The privacy protection of the Biometric Data is an important research topic, especially in the case of distributed Biometric systems. In this scenario, it is very important to guarantee that Biometric Data cannot be steeled by anyone, and that the Biometric clients are unable to gather any information different from the single user verification/identification. In a biométrie system with high level of privacy compliance, also the server that processes the biométrie matching should not learn anything on the Database and it should be impossible for the server to exploit the resulting matching values in order to extract any knowledge about the user presence or behavior. Within this conceptual framework, in this paper we propose a novel complete demonstrator based on a distributed biométrie system that is capable to protect the privacy of the individuals by exploiting cryptosystems. The implemented system computes the matching task in the encrypted domain by exploiting homomorphic encryption and using Fingercode templates. The paper describes the design methodology of the demonstrator and the obtained results. The demonstrator has been fully implemented and tested in real applicative conditions. Experimental results show that this method is feasible in the cases where the privacy of the Data is more important than the accuracy of the system and the obtained computational time is satisfactory.