Relay attacks are nowadays well known and most designers of secure authentication protocols are aware of them. At present, the main methods to prevent these attacks are based on the so-called distance bounding technique which consists in measuring the round-trip time of the exchanged authentication messages between the prover and the verifier to estimate an upper bound on the distance between these entities. Based on this bound, the verifier checks if the prover is sufficiently close by to rule out an unauthorized entity. Recently, a new work has proposed an authentication protocol that surprisingly uses the side-channel leakage to prevent relay attacks. In this paper, we exhibit some practical and security issues of this protocol and provide a new one that fixes all of them. Then, we argue the resistance of our proposal against both side-channel and relay attacks under some realistic assumptions. Our experimental results show the efficiency of our protocol in terms of false acceptance and false rejection rates.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

The secure two-party computation (S2PC) protocols SHADE and GSHADE have been introduced by Bringer et al. in the last two years. The protocol GSHADE permits to compute different distances (Hamming, Euclidean, Mahalanobis) quite efficiently and is one of the most efficient compared to other S2PC methods. Thus this protocol can be used to efficiently compute one-to-many identification for several biometrics data (iris, face, fingerprint).

We propose a novel vein extraction technique adapted to template protection and use it to apply a fuzzy commitment scheme. We construct dedicated error correcting codes that enable us to maintain a good accuracy after template protection. In a second application, we offer to overcome the alignment issues when comparing two vein templates by performing this step outside of the protection scheme. Different implementations are proposed to explore trade-offs between False Rejection Rate, False Acceptance Rate, comparison time and security. All approaches are tested on the recent database of University of Twente from ICB 2013. Our biometric performances are close to state of the art approaches whilst bringing security with the template protection scheme.

Since the seminal paper of Ratha et al. in 2001 that introduced cancelable biometrics, inner permutation of biometric templates has been widely suggested as one of the basic components to protect biometric data against compromised or cross-checking between two databases. In this paper, we study the case of iris biometrics where an inner permutation corresponds to shuffling the bits of a template in order to diversify the stored data. We analyze the security brought by a permutation and underline the impact of non-uniformity of templates on the robustness of cancelable biometrics: we introduce new attack strategies on permuted biometric databases that enable to reconstruct part of the permutation, leading to a potential privacy leakage. We finally suggest ways to improve efficiently the protection, by designing specific countermeasures, with no impact on accuracy and a low impact on the overall architecture of the system.

At WAHC'13, Bringer et al. introduced a protocol called SHADE for secure and efficient Hamming distance computation using oblivious transfer only. In this paper, we introduce a generalization of the SHADE protocol, called GSHADE, that enables privacy-preserving computation of several distance metrics, including (normalized) Hamming distance, Euclidean distance, Mahalanobis distance, and scalar product. GSHADE can be used to efficiently compute one-to-many biometric identification for several traits (iris, face, fingerprint) and benefits from recent optimizations of oblivious transfer extensions. GSHADE allows identification against a database of 1000 Eigenfaces in 1.28 seconds and against a database of 10000 IrisCodes in 17.2 seconds which is more than 10 times faster than previous works.

Shamir proposed the setbase approach as a means of improving security and privacy of the traditional biometric system. In this paper, we propose privacy-preserving drawer size standards for the biometric setbase. The proposal incorporates database privacy metrics such as k-anonymity and l-diversity into the definition of privacy-preserving drawer size standard for the biometric setbase. We also empirically evaluate the system reliability of the prototype setbase for the purpose of studying the trade-off values between the level of privacy protection and the level of system security.

This paper presents a moderately secure but very efficient approximate nearest neighbors search. After detailing the threats pertaining to the `honest but curious' model, our approach starts from a state-of-the-art algorithm in the domain of approximate nearest neighbors search. We gradually develop mechanisms partially blocking the attacks threatening the original algorithm.

Shamir proposed the setbase approach as a means of improving security and privacy of the traditional biometric system. As a result of the limitation of the current setbase filling procedure, we demonstrate that there are potential privacy weaknesses due to non-default distributions on attributes inside the identity database. We introduce in this paper, the concept of ϵ-closeness as a general framework to describe quantitatively the distribution anomaly. As a consequence, we are able to formulate a privacy-preserving drawer size standard for the setbase that includes the non-default distribution cases.

In 2009, Shamir proposed the setbase approach to protect the privacy of biometric data during ID documents issuance. One year later, Bringer and Chabanne introduced negative databases for biometric data. In this paper, we show that negative database techniques can also be applied to the setbase approach to enforce some of its security characteristics.

In this correspondence, we analyze the vulnerabilities of biometric authentication protocols with respect to user and data privacy. The goal of an adversary in such context is not to bypass the authentication but to learn information either on biometric data or on users that are in the system. We elaborate our analysis on a general system model involving four logical entities (sensor, server, database, and matcher), and we focus on internal adversaries to encompass the situation where one or a combination of these entities would be malicious. Our goal is to emphasize that when going beyond the usual honest-but-curious assumption much more complex attacks can affect the privacy of data and users. On the one hand, we introduce a new comprehensive framework that encompasses the various schemes we want to look at. It presents a system model in which each internal entity or combination of entities is a potential attacker. Different attack goals are considered and resulting requirements on data flows are discussed. On the other hand, we develop different generic attacks. We follow a blackbox approach in which we consider components that perform operations on biometric data but where only the input/output behavior is analyzed. These attack strategies are exhibited on recent schemes such as the distributed protocol of Bringer (ACISP 2007), which is based on the Goldwasser-Micali cryptosystem, the related protocol of Barbosa (ACISP 2008), which uses the Paillier cryptosystem, and the scheme of Stoianov (SPIE 2010), that features the Blum-Goldwasser cryptosystem. All these schemes have been developed in the honest-but-curious adversary model and show potential weaknesses when considered in our malicious insider attack model.

At ITW'10, Bringer suggested to strengthen their previous identification protocol where the security depends on computational assumptions (related to the Polynomial Reconstruction problem) by extending the Code Reverse Engineering (CRE) problem to identification codes. We formalize this new problem and we extend security results by Tillich on this very problem. This enables us to prove the security of this protocol using information theoretical arguments.

Abstract Biometrics make human identification possible with a sample of a biometric trait and an associated database. Classical identification techniques lead to privacy concerns. This paper introduces a new method to identify someone using his biometrics in an encrypted way. Our construction combines Bloom Filters with Storage and Locality‐Sensitive Hashing. We apply this error‐tolerant scheme, in a Hamming space, to achieve biometric identification in an efficient way. This is the first non‐trivial identification scheme dealing with fuzziness and encrypted data. Copyright © 2010 John Wiley & Sons, Ltd.

Identification codes were introduced by Ahlswede and Dueck more than twenty years ago. There is today a lot of studies to identify objects such as contactless devices (for instance RFID tags) but, surprisingly, no one has considered the use of this kind of codes in the literature for that purpose until the recent work of Bringer et al. at Indocrypt '09. We here show how the security of these new identification protocols is related to some well-known problems in coding theory. We also extend the original proposal to a new problem.

At first glance, privacy and zero-knowledgeness seem to be similar properties. A scheme is private when no information is revealed on the prover and in a zero-knowledge scheme, communications should not leak provers' secrets.

In this paper, we describe a new primitive for error-tolerant searchable encryption and a security model for it. This generic scheme permits to make searches on encrypted data with only an approximation of some keyword. It enables to efficiently query secure databases in order to get the exact data with a close estimation of it. An application to biometric identification arises from this construction. This is the first construction both for error-tolerant searchable encryption and for a biometric identification protocol over encrypted personal data.

Fuzzy commitment schemes, introduced as a link between biometrics and cryptography, are a way to handle biometric data matching as an error-correction issue. We focus here on finding the best error-correcting code with respect to a given database of biometric data. We propose a method that models discrepancies between biometric measurements as an erasure and error channel, and we estimate its capacity. We then show that two-dimensional iterative min-sum decoding of properly chosen product codes almost reaches the capacity of this channel. This leads to practical fuzzy commitment schemes that are close to theoretical limits. We test our techniques on public iris and fingerprint databases and validate our findings.

HB+is a lightweight protocol secure against active attacks but only in a detection based model. Since its introduction at Crypto'05 by Juels and Weis, many workers have tried to enhance its security. We here propose a new approach to achieve resistance against man-in-the-middle (MITM) attacks. Our requirements - in terms of extra communications and hardware - are surprisingly low.

In 1999, Juels and Wattenberg introduce an effective construction of Fuzzy Sketch, i.e., a way of handling errors into string verification. This allows them to consider data varying in time, such as, for instance, answers to a list of subjective questions. To this end, they use an error-correcting code. We show here how to embed a trapdoor into Fuzzy Sketches, reducing to authorized people the ability to correct errors and thus to verify the fuzzy equality to the Fuzzy Sketch.