Audio- and video-based biometric person authentication

Introduction to real analysis

Some readers know to play the game of nim well, fewer play a perfect annihilation game, and nobody knows whether there exists an opening move in chess that will guarantee a win for white. These games and many more, belong to the family of combinatorial games, by which we mean the set of all two-player perfect-information games without chance moves and with outcomes lose or win (and sometimes: dynamic tie). The motivation for ONAG may have been, and perhaps was-and I would like to think that it was-the attempt to bridge the theory gap between nim-like and chess-like games. Why is there a gap? Every combinatorial game can be described as a directed graph called game-graph, whose vertices are the game positions, and (u, v) is a directed edge if and only if there is a move from position u to position v. Denote by N the set of all positions from which the Next (first) player can force a win; by P the set of all positions from which the Previous (second) player can force a win; and by T the set of all (dynamic) Tie positions, which are positions from which no player can force a win and therefore both can avoid losing. In an acyclic game-graph there cannot be any tie positions. The N, P, T classification of any game graph R = (V, E) can be determined in 0(\V\ + \E\) steps [8]. For both nim and chess, a finite game-graph can be constructed and the N, P, T classification can be determined. So both games are solvable in principle. If we play nim with n piles, each pile containing at most k tokens, then the game-graph contains (k + \) vertices. Suppose that in (generalized) chess played on an « X « board there are k different pieces. If k is about n/2, then the game-graph of chess contains O (2") vertices. So both game-graphs have exponentially many vertices, and thus both games appear intractable in the usual sense of computational complexity [1, Chapter 10], [14, Chapter 9], namely a computation appears to be required which is asymptotically exponential. From a computational efficiency standpoint, the essential difference between nim and chess is that nim can be viewed as a disjunctive compound (sum) of independent games, namely the individual piles. A disjunctive

http://ieeexplore.ieee.org/iel5/5/31266/01455274.pdf

On numbers and games

In biometric identification systems, the biometric database is typically stored in a trusted server, which is also responsible for performing the identification process. However, a standalone server may not be able to provide enough storage and processing power for large databases. Nowadays, cloud computing and storage solutions have provided users and enterprises with various capabilities to store and process their data in third-party data centers. However, maintenance of the confidentiality and integrity of sensitive data requires trustworthy solutions for storage and processing of data with proven zero information leakage. In this paper, we present CloudID, a privacy-preserving cloud-based and cross-enterprise biometric identification solution. It links the confidential information of the users to their biometrics and stores it in an encrypted fashion. Making use of a searchable encryption technique, biometric identification is performed in encrypted domain to make sure that the cloud provider or potential attackers do not gain access to any sensitive data or even the contents of the individual queries. In order to create encrypted search queries, we propose a k-d tree structure in the core of the searchable encryption. This helps not only in handling the biometrics variations in encrypted domain, but also in improving the overall performance of the system. Our proposed approach is the first cloud-based biometric identification system with a proven zero data disclosure possibility. It allows different enterprises to perform biometric identification on a single database without revealing any sensitive information. Our experimental results show that CloudID performs the identification of clients with high accuracy and minimal overhead and proven zero data disclosure.

CloudID: Trustworthy cloud-based and cross-enterprise biometric identification

We describe a lightweight protocol for oblivious evaluation of a pseudorandom function (OPRF) in the presence of semihonest adversaries. In an OPRF protocol a receiver has an input r; the sender gets output s and the receiver gets output F(s; r), where F is a pseudorandom function and s is a random seed. Our protocol uses a novel adaptation of 1-out-of-2 OT-extension protocols, and is particularly efficient when used to generate a large batch of OPRF instances. The cost to realize m OPRF instances is roughly the cost to realize 3:5m instances of standard 1-out-of-2 OTs (using state-of-the-art OT extension). We explore in detail our protocol's application to semihonest secure private set intersection (PSI). The fastest state-of- the-art PSI protocol (Pinkas et al., Usenix 2015) is based on efficient OT extension. We observe that our OPRF can be used to remove their PSI protocol's dependence on the bit-length of the parties' items. We implemented both PSI protocol variants and found ours to be 3.1{3.6 faster than Pinkas et al. for PSI of 128-bit strings and sufficiently large sets. Concretely, ours requires only 3.8 seconds to securely compute the intersection of 220-size sets, regardless of the bitlength of the items. For very large sets, our protocol is only 4:3 slower than the insecure naive hashing approach for PSI.

/pdf/efficient-batched-oblivious-prf-with-applications-to-private-3goewrwuoh.pdf

Efficient Batched Oblivious PRF with Applications to Private Set Intersection.

Homomorphic authenticators HAs enable a client to authenticate a large collection of data elements $$m_1, \ldots , m_t$$ and outsource them, along with the corresponding authenticators, to an untrusted server. At any later point, the server can generate a short authenticator vouching for the correctness of the output y of a function f computed on the outsourced data, i.e., $$y=fm_1, \ldots , m_t$$. Recently researchers have focused on HAs as a solution, with minimal communication and interaction, to the problem of delegating computation on outsourced data. The notion of HAs studied so far, however, only supports executions and proofs of correctness of computations over data authenticated by a single user. Motivated by realistic scenarios ubiquitous computing, sensor networks, etc. in which large datasets include data provided by multiple users, we study the concept of multi-key homomorphic authenticators. In a nutshell, multi-key HAs are like HAs with the extra feature of allowing the holder of public evaluation keys to compute on data authenticated under different secret keys. In this paper, we introduce and formally define multi-key HAs. Secondly, we propose a construction of a multi-key homomorphic signature based on standard lattices and supporting the evaluation of circuits of bounded polynomial depth. Thirdly, we provide a construction of multi-key homomorphic MACs based only on pseudorandom functions and supporting the evaluation of low-degree arithmetic circuits. Albeit being less expressive and only secretly verifiable, the latter construction presents interesting efficiency properties.

/pdf/multi-key-homomorphic-authenticators-4r0v9imwlx.pdf

Multi-key Homomorphic Authenticators

In biometric authentication protocols, a user is authenticated or granted access to a service if her fresh biometric trait matches the reference biometric template stored on the service provider. This matching process is usually based on a suitable distance which measures the similarities between the two biometric templates. In this paper, we prove that, when the matching process is performed using a specific family of distances (which includes distances such as the Hamming and the Euclidean distance), then information about the reference template is leaked. This leakage of information enables a hill-climbing attack that, given a sample that matches the template, could lead to the full recovery of the biometric template (i.e. centre search attack) even if it is stored encrypted. We formalise this “leakage of information" in a mathematical framework and we prove that centre search attacks are feasible for any biometric template defined in $\mathbb {Z}_q^n, (q\ge 2)$ after a number of authentication attempts linear in $n$. Furthermore, we investigate brute force attacks to find a biometric template that matches a reference template, and hence can be used to run a centre search attack. We do this in the binary case and identify connections with the set-covering problem and sampling without replacement.

/pdf/on-the-leakage-of-information-in-biometric-authentication-3wgwygitvn.pdf

On the Leakage of Information in Biometric Authentication

An emerging direction for authenticating people is the adoption of biometric authentication systems. Biometric credentials are becoming increasingly popular as a means of authenticating people due to the wide range of advantages that they provide with respect to classical authentication methods (e.g., password-based authentication). The most characteristic feature of this authentication method is the naturally strong bond between a user and her biometric credentials. This very same advantageous property, however, raises serious security and privacy concerns in case the biometric trait gets compromised. In this article, we present the most challenging issues that need to be taken into consideration when designing secure and privacy-preserving biometric authentication protocols. More precisely, we describe the main threats against privacy-preserving biometric authentication systems and give directions on possible countermeasures in order to design secure and privacy-preserving biometric authentication protocols.

/pdf/privacy-preserving-biometric-authentication-challenges-and-51izhnss96.pdf

Privacy-Preserving Biometric Authentication: Challenges and Directions

Authentication in wireless communications often depends on the physical proximity to a location. Distance-bounding ( $\mathsf{DB}$ ) protocols are cross-layer authentication protocols that are based on the round-trip-time of challenge-response exchanges and can be employed to guarantee physical proximity and combat relay attacks. However, traditional $\mathsf{DB}$ protocols rely on the assumption that the prover (e.g., user) is in the communication range of the verifier (e.g., access point); something that might not be the case in multiple access control scenarios in ubiquitous computing environments as well as when we need to verify the proximity of our two-hop neighbour in an ad-hoc network. In this paper, we extend traditional $\mathsf{DB}$ protocols to a two-hop setting, i.e., when the prover is out of the communication range of the verifier and thus, they both need to rely on an untrusted in-between entity in order to verify proximity. We present a formal framework that captures the most representative classes of existing $\mathsf{DB}$ protocols and provide a general method to extend traditional $\mathsf{DB}$ protocols to the two-hop case (three participants). We analyze the security of two-hop $\mathsf{DB}$ protocols and identify connections with the security issues of the corresponding one-hop case. Finally, we demonstrate the correctness of our security analysis and the efficiency of our model by transforming five existing $\mathsf{DB}$ protocols to the two-hop setting and we evaluate their performance with simulated experiments.

/pdf/two-hop-distance-bounding-protocols-keep-your-friends-close-5dq749z7o5.pdf

Two-Hop Distance-Bounding Protocols: Keep Your Friends Close

Ridesharing is revolutionizing the transportation industry in many countries. Yet, the state of the art is based on heavily centralized services and platforms, where the service providers have full possession of the users’ location data. Recently, researchers have started addressing the challenge of enabling privacy-preserving ridesharing. The initial proposals, however, have shortcomings, as some rely on a central party, some incur high performance penalties, and most do not consider time preferences for ridesharing. TOPPool encompasses ridesharing based on the proximity of end-points of a ride as well as partial itinerary overlaps. To achieve the latter, we propose a simple yet powerful reduction to a private set intersection on trips represented as sets of consecutive road segments. We show that TOPPool includes time preferences while preserving privacy and without relying on a third party. We evaluate our approach on real-world data from the New York’s Taxi & Limousine Commission. Our experiments demonstrate that TOPPool is superior in performance over the prior work: our intersection-based itinerary matching runs in less than 0.3 seconds for reasonable trip length, in contrast, on the same set of trips prior work takes up to 10 hours. (Less)

https://www.sciendo.com/pdf/10.2478/popets-2019-0060

Elena Pagnin

Papers

Multi-key Homomorphic Authenticators

On the Leakage of Information in Biometric Authentication

Privacy-Preserving Biometric Authentication: Challenges and Directions

Two-Hop Distance-Bounding Protocols: Keep Your Friends Close

TOPPool: Time-aware Optimized Privacy-Preserving Ridesharing