530 research outputs found
Facial Template Protection via Lattice-based Fuzzy Extractors
With the growing adoption of facial recognition worldwide as a popular authentication method, there is increasing concern about the invasion of personal privacy due to the lifetime irrevocability of facial features.
In principle, {\it Fuzzy Extractors} enable biometric-based authentication while preserving the privacy of biometric templates.
Nevertheless, to our best knowledge, most existing fuzzy extractors handle binary vectors with Hamming distance, and no explicit construction is known for facial recognition applications where -distance of real vectors is considered.
In this paper, we utilize the dense packing feature of certain lattices (e.g., and Leech) to design a family of {\it lattice-based} fuzzy extractors that docks well with existing neural network-based biometric identification schemes.
We instantiate and implement the generic construction and conduct experiments on publicly available datasets. Our result confirms the feasibility of facial template protection via fuzzy extractors
Constructing practical Fuzzy Extractors using QIM
Fuzzy extractors are a powerful tool to extract randomness from noisy data. A fuzzy extractor can extract randomness only if the source data is discrete while in practice source data is continuous. Using quantizers to transform continuous data into discrete data is a commonly used solution. However, as far as we know no study has been made of the effect of the quantization strategy on the performance of fuzzy extractors. We construct the encoding and the decoding function of a fuzzy extractor using quantization index modulation (QIM) and we express properties of this fuzzy extractor in terms of parameters of the used QIM. We present and analyze an optimal (in the sense of embedding rate) two dimensional construction. Our 6-hexagonal tiling construction offers ( log2 6 / 2-1) approx. 3 extra bits per dimension of the space compared to the known square quantization based fuzzy extractor
Fuzzy Extractors: How to Generate Strong Keys from Biometrics and Other Noisy Data
We provide formal definitions and efficient secure techniques for
- turning noisy information into keys usable for any cryptographic
application, and, in particular,
- reliably and securely authenticating biometric data.
Our techniques apply not just to biometric information, but to any keying
material that, unlike traditional cryptographic keys, is (1) not reproducible
precisely and (2) not distributed uniformly. We propose two primitives: a
"fuzzy extractor" reliably extracts nearly uniform randomness R from its input;
the extraction is error-tolerant in the sense that R will be the same even if
the input changes, as long as it remains reasonably close to the original.
Thus, R can be used as a key in a cryptographic application. A "secure sketch"
produces public information about its input w that does not reveal w, and yet
allows exact recovery of w given another value that is close to w. Thus, it can
be used to reliably reproduce error-prone biometric inputs without incurring
the security risk inherent in storing them.
We define the primitives to be both formally secure and versatile,
generalizing much prior work. In addition, we provide nearly optimal
constructions of both primitives for various measures of ``closeness'' of input
data, such as Hamming distance, edit distance, and set difference.Comment: 47 pp., 3 figures. Prelim. version in Eurocrypt 2004, Springer LNCS
3027, pp. 523-540. Differences from version 3: minor edits for grammar,
clarity, and typo
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
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A schema for cryptographic keys generation using hybrid biometrics
Biometric identifiers refer to unique physical properties or behavioural attributes of individuals. Some of the well known biometric identifiers are voice, finger prints, retina or iris, facial structure etc. In our daily interaction with others directly or indirectly, we implicitly use biometrics to know, distinguish and trust people. Biometric identifiers represent the concept of "who a person is" by gathering vital characteristics that don't correspond to any other person. The human brain to some extent is able to ascertain disparities or variation in certain physical attributes and yet verify the authenticity of a person. But this is difficult to be implemented in electronic systems due to the intense requirements of artificial decision making and hard-coded logic.
This paper examines the possibility of using a combination of biometric attributes to overcome common problems in having a single biometric scheme for authentication. It also investigates possible schemes and features to deal with variations in Biometric attributes. The material presented is related to ongoing research by the Computer Communications Research Group at Leeds Metropolitan University. We use this paper as a starting step and as a plan for advanced research. It offers ideas and proposition for implementing hybrid biometrics in conjunction with cryptography. This is work in progress and is in a very preliminary stage
Leakage-resilient biometric-based remote user authentication with fuzzy extractors
National Research Foundation (NRF) Singapor
Coding Solutions for the Secure Biometric Storage Problem
The paper studies the problem of securely storing biometric passwords, such
as fingerprints and irises. With the help of coding theory Juels and Wattenberg
derived in 1999 a scheme where similar input strings will be accepted as the
same biometric. In the same time nothing could be learned from the stored data.
They called their scheme a "fuzzy commitment scheme". In this paper we will
revisit the solution of Juels and Wattenberg and we will provide answers to two
important questions: What type of error-correcting codes should be used and
what happens if biometric templates are not uniformly distributed, i.e. the
biometric data come with redundancy. Answering the first question will lead us
to the search for low-rate large-minimum distance error-correcting codes which
come with efficient decoding algorithms up to the designed distance. In order
to answer the second question we relate the rate required with a quantity
connected to the "entropy" of the string, trying to estimate a sort of
"capacity", if we want to see a flavor of the converse of Shannon's noisy
coding theorem. Finally we deal with side-problems arising in a practical
implementation and we propose a possible solution to the main one that seems to
have so far prevented real life applications of the fuzzy scheme, as far as we
know.Comment: the final version appeared in Proceedings Information Theory Workshop
(ITW) 2010, IEEE copyrigh
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