37 research outputs found
SHE based Non Interactive Privacy Preserving Biometric Authentication Protocols
Being unique and immutable for each person, biometric signals are widely used in access control systems. While biometric recognition appeases concerns about password's theft or loss, at the same time it raises concerns about individual privacy. Central servers store several enrolled biometrics, hence security against theft must be provided during biometric transmission and against those who have access to the database. If a server's database is compromised, other systems using the same biometric templates could also be compromised as well. One solution is to encrypt the stored templates. Nonetheless, when using traditional cryptosystem, data must be decrypted before executing the protocol, leaving the database vulnerable. To overcame this problem and protect both the server and the client, biometrics should be processed while encrypted. This is possible by using secure two-party computation protocols, mainly based on Garbled Circuits (GC) and additive Homomorphic Encryption (HE). Both GC and HE based solutions are efficient yet interactive, meaning that the client takes part in the computation. Instead in this paper we propose a non-interactive protocol for privacy preserving biometric authentication based on a Somewhat Homomorphic Encryption (SHE) scheme, modified to handle integer values, and also suggest a blinding method to protect the system from spoofing attacks. Although our solution is not as efficient as the ones based on GC or HE, the protocol needs no interaction, moving the computation entirely on the server side and leaving only inputs encryption and outputs decryption to the client
Homomorphic Encryption for Speaker Recognition: Protection of Biometric Templates and Vendor Model Parameters
Data privacy is crucial when dealing with biometric data. Accounting for the
latest European data privacy regulation and payment service directive,
biometric template protection is essential for any commercial application.
Ensuring unlinkability across biometric service operators, irreversibility of
leaked encrypted templates, and renewability of e.g., voice models following
the i-vector paradigm, biometric voice-based systems are prepared for the
latest EU data privacy legislation. Employing Paillier cryptosystems, Euclidean
and cosine comparators are known to ensure data privacy demands, without loss
of discrimination nor calibration performance. Bridging gaps from template
protection to speaker recognition, two architectures are proposed for the
two-covariance comparator, serving as a generative model in this study. The
first architecture preserves privacy of biometric data capture subjects. In the
second architecture, model parameters of the comparator are encrypted as well,
such that biometric service providers can supply the same comparison modules
employing different key pairs to multiple biometric service operators. An
experimental proof-of-concept and complexity analysis is carried out on the
data from the 2013-2014 NIST i-vector machine learning challenge
THRIVE: Threshold Homomorphic encryption based secure and privacy preserving bIometric VErification system
In this paper, we propose a new biometric verification and template
protection system which we call the THRIVE system. The system includes novel
enrollment and authentication protocols based on threshold homomorphic
cryptosystem where the private key is shared between a user and the verifier.
In the THRIVE system, only encrypted binary biometric templates are stored in
the database and verification is performed via homomorphically randomized
templates, thus, original templates are never revealed during the
authentication stage. The THRIVE system is designed for the malicious model
where the cheating party may arbitrarily deviate from the protocol
specification. Since threshold homomorphic encryption scheme is used, a
malicious database owner cannot perform decryption on encrypted templates of
the users in the database. Therefore, security of the THRIVE system is enhanced
using a two-factor authentication scheme involving the user's private key and
the biometric data. We prove security and privacy preservation capability of
the proposed system in the simulation-based model with no assumption. The
proposed system is suitable for applications where the user does not want to
reveal her biometrics to the verifier in plain form but she needs to proof her
physical presence by using biometrics. The system can be used with any
biometric modality and biometric feature extraction scheme whose output
templates can be binarized. The overall connection time for the proposed THRIVE
system is estimated to be 336 ms on average for 256-bit biohash vectors on a
desktop PC running with quad-core 3.2 GHz CPUs at 10 Mbit/s up/down link
connection speed. Consequently, the proposed system can be efficiently used in
real life applications
Biometric privacy protection : guidelines and technologies
Compared with traditional techniques used to establish the identity of a person, biometric systems offer a greater confidence level that the authenticated individual is not impersonated by someone else. However, it is necessary to consider different privacy and security aspects in order to prevent possible thefts and misuses of biometric data. The effective protection of the privacy must encompass different aspects, such as the perceived and real risks pertaining to the users, the specificity of the application, the adoption of correct policies, and data protection methods as well. This chapter focuses on the most important privacy issues related to the use of biometrics, it presents actual guidelines for the implementation of privacy-protective biometric systems, and proposes a discussion of the methods for the protection of biometric data
Security and Efficiency Analysis of the Hamming Distance Computation Protocol Based on Oblivious Transfer
open access articleBringer et al. proposed two cryptographic protocols for the computation of Hamming distance. Their first scheme uses Oblivious Transfer and provides security in the semi-honest model. The other scheme uses Committed Oblivious Transfer and is claimed to provide full security in the malicious case. The proposed protocols have direct implications to biometric authentication schemes between a prover and a verifier where the verifier has biometric data of the users in plain form.
In this paper, we show that their protocol is not actually fully secure against malicious adversaries. More precisely, our attack breaks the soundness property of their protocol where a malicious user can compute a Hamming distance which is different from the actual value. For biometric authentication systems, this attack allows a malicious adversary to pass the authentication without knowledge of the honest user's input with at most complexity instead of , where is the input length. We propose an enhanced version of their protocol where this attack is eliminated. The security of our modified protocol is proven using the simulation-based paradigm. Furthermore, as for efficiency concerns, the modified protocol utilizes Verifiable Oblivious Transfer which does not require the commitments to outputs which improves its efficiency significantly
Privacy-Aware Processing of Biometric Templates by Means of Secure Two-Party Computation
The use of biometric data for person identification and access control is gaining more and more popularity. Handling biometric data, however, requires particular care, since biometric data is indissolubly tied to the identity of the owner hence raising important security and privacy issues. This chapter focuses on the latter, presenting an innovative approach that, by relying on tools borrowed from Secure Two Party Computation (STPC) theory, permits to process the biometric data in encrypted form, thus eliminating any risk that private biometric information is leaked during an identification process. The basic concepts behind STPC are reviewed together with the basic cryptographic primitives needed to achieve privacy-aware processing of biometric data in a STPC context. The two main approaches proposed so far, namely homomorphic encryption and garbled circuits, are discussed and the way such techniques can be used to develop a full biometric matching protocol described. Some general guidelines to be used in the design of a privacy-aware biometric system are given, so as to allow the reader to choose the most appropriate tools depending on the application at hand
Privacy-preserving comparison of variable-length data with application to biometric template protection
The establishment of cloud computing and big data in a wide variety of daily applications has raised some privacy concerns due to the sensitive nature of some of the processed data. This has promoted the need to develop data protection techniques, where the storage and all operations are carried out without disclosing any information. Following this trend, this paper presents a new approach to efficiently compare variable-length data in the encrypted domain using homomorphic encryption where only encrypted data is stored or exchanged. The new variable-length-based algorithm is fused with existing fixed-length techniques in order to obtain increased comparison accuracy. To assess the soundness of the proposed approach, we evaluate its performance on a particular application: a multi-algorithm biometric template protection system based on dynamic signatures that complies with the requirements described in the ISO/IEC 24745 standard on biometric information protection. Experiments have been carried out on a publicly available database and a free implementation of the Paillier cryptosystem to ensure reproducibility and comparability to other schemes.This work was supported in part by the German Federal Ministry of Education and Research (BMBF); in part by the Hessen State Ministry
for Higher Education, Research, and the Arts (HMWK) within the Center for Research in Security and Privacy (CRISP); in part by the
Spanish Ministerio de Economia y Competitividad / Fondo Europeo de Desarrollo Regional through the CogniMetrics Project under Grant
TEC2015-70627-R; and in part by Cecaban
Fingerprint template protection schemes: A literature review
The fingerprint is the most widely used technology for identification or authentication systems, which can be known as fingerprint authentication systems (FAS).In addition to providing security, the fingerprint is also easy to use, very reliable and has a high accuracy for identity recognition. FAS is still exposed to security attacks because fingerprint information is unencrypted.Therefore, fingerprint information requires protection known as fingerprint template protection (FTP).This paper aims to provide an organized literature on FTP.Three research questions were formulated to guide the literature analysis.First, this
analysis focuses on the types of FTP schemes; second, the metrics used for evaluating the FTP schemes; and finally, the common datasets used for evaluating the FTP schemes. The latest information and references are analysed and classified based on FTP methods and publication year to obtain information related to the development and application of FTP.This study mainly surveyed 62 documents reported on FTP schemes between the year 2000 and 2017.The results of this survey can be a source of reference for other researchers in finding literature relevant to the FTP