Pseudo Identities Based on Fingerprint Characteristics

This paper presents the integrated project TURBINE which is funded under the EU 7th research framework programme. This research is a multi-disciplinary effort on privacy enhancing technology, combining innovative developments in cryptography and fingerprint recognition. The objective of this project is to provide a breakthrough in electronic authentication for various applications in the physical world and on the Internet. On the one hand it will provide secure identity verification thanks to fingerprint recognition. On the other hand it will reliably protect the biometric data through advanced cryptography technology. In concrete terms, it will provide the assurance that (i) the data used for the authentication, generated from the fingerprint, cannot be used to restore the original fingerprint sample, (ii) the individual will be able to create different "pseudo-identities" for different applications with the same fingerprint, whilst ensuring that these different identities (and hence the related personal data) cannot be linked to each other, and (iii) the individual is enabled to revoke an biometric identifier (pseudo-identity) for a given application in case it should not be used anymore

State of the Art in Biometric Key Binding and Key Generation Schemes

Direct storage of biometric templates in databases exposes the authentication system and legitimate users to numerous security and privacy challenges. Biometric cryptosystems or template protection schemes are used to overcome the security and privacy challenges associated with the use of biometrics as a means of authentication. This paper presents a review of previous works in biometric key binding and key generation schemes. The review focuses on key binding techniques such as biometric encryption, fuzzy commitment scheme, fuzzy vault and shielding function. Two categories of key generation schemes considered are private template and quantization schemes. The paper also discusses the modes of operations, strengths and weaknesses of various kinds of key-based template protection schemes. The goal is to provide the reader with a clear understanding of the current and emerging trends in key-based biometric cryptosystems

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

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

Biometric Fuzzy Extractor Scheme for Iris Templates

In: The 2009 World Congress in Computer Science, Computer Engineering, and Applied Computing (WORLDCOMP'09), The 2009 International Conference on Security and Management (SAM'09), Vol II, Proceedings 563--569. H.R. Arabnia and K. Daimi (Eds.), Las Vegas (USA), July, 2009Biometric recognition offers a reliable and natural solution to the problem of user authentication by means of her physical and behavioral traits. An iris template protection scheme which associates and retrieves a secret value with a high level of security, is proposed. The security is guaranteed thanks to the requirements of fuzzy extractors. The implementation of the scheme is done in Java and experimental results are performed to calculate its False Acceptance Rate and its False Rejection Rate.This work has been partially supported by Ministerio de Industria, Turismo y Comercio (Spain), in collaboration with CDTI and Telefónica I+D under the project SEGUR@ (CENIT-2007 2004).Peer reviewe

Privacy Protection in Distributed Fingerprint-based Authentication

Biometric authentication is getting increasingly popular due to the convenience of using unique individual traits, such as fingerprints, palm veins, irises. Especially fingerprints are widely used nowadays due to the availability and low cost of fingerprint scanners. To avoid identity theft or impersonation, fingerprint data is typically stored locally, e.g., in a trusted hardware module, in a single device that is used for user enrollment and authentication. Local storage, however, limits the ability to implement distributed applications, in which users can enroll their fingerprint once and use it to access multiple physical locations and mobile applications afterwards. In this paper, we present a distributed authentication system that stores fingerprint data in a server or cloud infrastructure in a privacy-preserving way. Multiple devices can be connected and perform user enrollment or verification. To secure the privacy and integrity of sensitive data, we employ a cryptographic construct called fuzzy vault. We highlight challenges in implementing fuzzy vault-based authentication, for which we propose and compare alternative solutions. We conduct a security analysis of our biometric cryptosystem, and as a proof of concept, we build an authentication system for access control using resource-constrained devices (Raspberry Pis) connected to fingerprint scanners and the Microsoft Azure cloud environment. Furthermore, we evaluate the fingerprint matching algorithm against the well-known FVC2006 database and show that it can achieve comparable accuracy to widely-used matching techniques that are not designed for privacy, while remaining efficient with an authentication time of few seconds.Comment: This is an extended version of the paper with the same title which has been accepted for publication at the Workshop on Privacy in the Electronic Society (WPES 2019

Protection of privacy in biometric data

Biometrics is commonly used in many automated veri cation systems offering several advantages over traditional veri cation methods. Since biometric features are associated with individuals, their leakage will violate individuals\u27 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