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Fuzzy extractors: How to generate strong keys from biometrics and other noisy data
, 2008
"... 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 mater ..."
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Cited by 535 (38 self)
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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 errortolerant 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 errorprone 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.
Biometric template security,”
 EURASIP,
, 2008
"... Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance ..."
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Cited by 132 (11 self)
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Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a highlevel categorization of the various vulnerabilities of a biometric system and discuss countermeasures that have been proposed to address these vulnerabilities. In particular, we focus on biometric template security which is an important issue because, unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. Protecting the template is a challenging task due to intrauser variability in the acquired biometric traits. We present an overview of various biometric template protection schemes and discuss their advantages and limitations in terms of security, revocability, and impact on matching accuracy. A template protection scheme with provable security and acceptable recognition performance has thus far remained elusive. Development of such a scheme is crucial as biometric systems are beginning to proliferate into the core physical and information infrastructure of our society.
Combining crypto with biometrics effectively
 IEEE Trans. on Computers
, 2006
"... Abstract—We propose the first practical and secure way to integrate the iris biometric into cryptographic applications. A repeatable binary string, which we call a biometric key, is generated reliably from genuine iris codes. A wellknown difficulty has been how to cope with the 10 to 20 percent of ..."
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Cited by 112 (3 self)
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Abstract—We propose the first practical and secure way to integrate the iris biometric into cryptographic applications. A repeatable binary string, which we call a biometric key, is generated reliably from genuine iris codes. A wellknown difficulty has been how to cope with the 10 to 20 percent of error bits within an iris code and derive an errorfree key. To solve this problem, we carefully studied the error patterns within iris codes and devised a twolayer error correction technique that combines Hadamard and ReedSolomon codes. The key is generated from a subject’s iris image with the aid of auxiliary errorcorrection data, which do not reveal the key and can be saved in a tamperresistant token, such as a smart card. The reproduction of the key depends on two factors: the iris biometric and the token. The attacker has to procure both of them to compromise the key. We evaluated our technique using iris samples from 70 different eyes, with 10 samples from each eye. We found that an errorfree key can be reproduced reliably from genuine iris codes with a 99.5 percent success rate. We can generate up to 140 bits of biometric key, more than enough for 128bit AES. The extraction of a repeatable binary string from biometrics opens new possible applications, where a strong binding is required between a person and cryptographic operations. For example, it is possible to identify individuals without maintaining a central database of biometric templates, to which privacy objections might be raised.
Reusable cryptographic fuzzy extractors
 ACM CCS 2004, ACM
, 2004
"... We show that a number of recent definitions and constructions of fuzzy extractors are not adequate for multiple uses of the same fuzzy secret—a major shortcoming in the case of biometric applications. We propose two particularly stringent security models that specifically address the case of fuzzy s ..."
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Cited by 96 (2 self)
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We show that a number of recent definitions and constructions of fuzzy extractors are not adequate for multiple uses of the same fuzzy secret—a major shortcoming in the case of biometric applications. We propose two particularly stringent security models that specifically address the case of fuzzy secret reuse, respectively from an outsider and an insider perspective, in what we call a chosen perturbation attack. We characterize the conditions that fuzzy extractors need to satisfy to be secure, and present generic constructions from ordinary building blocks. As an illustration, we demonstrate how to use a biometric secret in a remote error tolerant authentication protocol that does not require any storage on the client’s side. 1
Secure remote authentication using biometric data
 In EUROCRYPT
, 2005
"... We show two efficient techniques enabling the use of biometric data to achieve mutual authentication or authenticated key exchange over a completely insecure (i.e., adversarially controlled) channel. In addition to achieving stronger security guarantees than the work of Boyen, we improve upon his so ..."
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Cited by 86 (13 self)
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We show two efficient techniques enabling the use of biometric data to achieve mutual authentication or authenticated key exchange over a completely insecure (i.e., adversarially controlled) channel. In addition to achieving stronger security guarantees than the work of Boyen, we improve upon his solution in a number of other respects: we tolerate a broader class of errors and, in one case, improve upon the parameters of his solution and give a proof of security in the standard model. 1 Using Biometric Data for Secure Authentication Biometric data, as a potential source of highentropy, secret information, havebeen suggested as a way to enable strong, cryptographicallysecure authentication of human users without requiring them to remember or store traditionalcryptographic keys. Before such data can be used in existing cryptographic protocols, however, two issues must be addressed: first, biometric data are not uniformly distributed and hence do not offer provable security guarantees if used
Cracking fuzzy vaults and biometric encryption
 In Proc. of the 2007 Biometrics Symposium, held in conjunction with the Biometrics Consortium Conference (BCC
, 2007
"... © 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to ..."
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Cited by 71 (7 self)
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© 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Preprint of article that appeared at the Biometrics Symposium 2007. The published article can be accessed from:
Correcting errors without leaking partial information
 In 37th Annual ACM Symposium on Theory of Computing (STOC
, 2005
"... This paper explores what kinds of information two parties must communicate in order to correct errors which occur in a shared secret string W. Any bits they communicate must leak a significant amount of information about W — that is, from the adversary’s point of view, the entropy of W will drop sig ..."
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Cited by 65 (9 self)
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This paper explores what kinds of information two parties must communicate in order to correct errors which occur in a shared secret string W. Any bits they communicate must leak a significant amount of information about W — that is, from the adversary’s point of view, the entropy of W will drop significantly. Nevertheless, we construct schemes with which Alice and Bob can prevent an adversary from learning any useful information about W. Specifically, if the entropy of W is sufficiently high, then there is no function f(W) which the adversary can learn from the errorcorrection information with significant probability. This leads to several new results: (a) the design of noisetolerant “perfectly oneway” hash functions in the sense of Canetti et al. [7], which in turn leads to obfuscation of proximity queries for high entropy secrets W; (b) private fuzzy extractors [11], which allow one to extract uniformly random bits from noisy and nonuniform data W, while also insuring that no sensitive information about W is leaked; and (c) noise tolerance and stateless key reuse in the Bounded Storage Model, resolving the main open problem of Ding [10]. The heart of our constructions is the design of strong randomness extractors with the property that the source W can be recovered from the extracted randomness and any string W ′ which is close to W.
Fuzzy Identity Based Encryption
, 2004
"... We introduce a new type of Identity Based Encryption (IBE) scheme that we call Fuzzy Identity Based Encryption. A Fuzzy IBE scheme allows for a private key for an identity id to decrypt a ciphertext encrypted with another identity id # if and only if the identities id and id # are close to each othe ..."
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Cited by 61 (8 self)
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We introduce a new type of Identity Based Encryption (IBE) scheme that we call Fuzzy Identity Based Encryption. A Fuzzy IBE scheme allows for a private key for an identity id to decrypt a ciphertext encrypted with another identity id # if and only if the identities id and id # are close to each other as measured by some metric (e.g. Hamming distance). A Fuzzy IBE scheme can be applied to enable encryption using biometric measurements as identities. The errortolerance of a Fuzzy IBE scheme is precisely what allows for the use of biometric identities, which inherently contain some amount of noise during each measurement.
Location privacy via private proximity testing
 In NDSS
, 2011
"... We study privacypreserving tests for proximity: Alice can test if she is close to Bob without either party revealing any other information about their location. We describe several secure protocols that support private proximity testing at various levels of granularity. We study the use of “locatio ..."
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Cited by 53 (1 self)
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We study privacypreserving tests for proximity: Alice can test if she is close to Bob without either party revealing any other information about their location. We describe several secure protocols that support private proximity testing at various levels of granularity. We study the use of “location tags ” generated from the physical environment in order to strengthen the security of proximity testing. We implemented our system on the Android platform and report on its effectiveness. Our system uses a social network (Facebook) to manage user public keys. 1
Combining cryptography with biometrics effectively
, 2005
"... We propose the first practical and secure way to integrate the iris biometric into cryptographic applications. A repeatable binary string, which we call a biometric key, is generated reliably from genuine iris codes. A wellknown difficulty has been how to cope with the 10 to 20 % of error bits with ..."
Abstract

Cited by 52 (0 self)
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We propose the first practical and secure way to integrate the iris biometric into cryptographic applications. A repeatable binary string, which we call a biometric key, is generated reliably from genuine iris codes. A wellknown difficulty has been how to cope with the 10 to 20 % of error bits within an iris code and derive an errorfree key. To solve this problem, we carefully studied the error patterns within iris codes, and devised a twolayer error correction technique that combines Hadamard and ReedSolomon codes. The key is generated from a subject’s iris image with the aid of auxiliary errorcorrection data, which do not reveal the key, and can be saved in a tamperresistant token such as a smart card. The reproduction of the key depends on two factors: the iris biometric and the token. The attacker has to procure both of them to compromise the key. We evaluated our technique using iris samples from 70 different eyes, with 10 samples from each eye. We found that an errorfree key can be reproduced reliably from genuine iris codes with a 99.5% success rate. We can generate up to 140 bits of biometric key, more than enough for 128bit AES. The extraction of a repeatable binary string from biometrics opens new possible applications, where a strong binding is required between a person and cryptographic operations. For example, it is possible to identify individuals without maintaining a central database of biometric templates, to which privacy objections might be raised.