A dynamic fuzzy commitment scheme using multiple commitments

Choto, Somsak; Premasathian, Nol

doi:10.1109/iscit.2012.6380912

Cited by 2 publications

(3 citation statements)

References 2 publications

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“…Experimental results show that the proposed scheme can be used to enhance the efficiency and security of BSNs. Enhanced versions of the fuzzy commitment scheme are based on dynamic use of multiple commitments [23] and the derivation of multiple commitments from a single commitment [24]. Security analysis show that these approaches provide improved security for stored biometric data because an attacker will need to compromise multiple encrypted templates and secret key before he can retrieve a secured biometric data.…”

Section: Fuzzy Commitment Schemementioning

confidence: 99%

“…Experimental results and security analysis reveal that these enhancements provide improved recognition and/or security of stored biometric data. A more secure version of the fuzzy commitment scheme derive a next commitment from the combination of the authenticated input and a current commitment [27]. The authors also proposed the alpha and beta smoothing methods.…”

Section: Fuzzy Commitment Schemementioning

confidence: 99%

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State of the Art in Biometric Key Binding and Key Generation Schemes

Jegede

Udzir

Abdullah

et al. 2022

Int. j. commun. netw. inf. secur.

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Direct storage of biometric templates in databases exposes the authentication system and legitimate users to numerous security and privacy challenges. Biometric cryptosystems or template protection schemes are used to overcome the security and privacy challenges associated with the use of biometrics as a means of authentication. This paper presents a review of previous works in biometric key binding and key generation schemes. The review focuses on key binding techniques such as biometric encryption, fuzzy commitment scheme, fuzzy vault and shielding function. Two categories of key generation schemes considered are private template and quantization schemes. The paper also discusses the modes of operations, strengths and weaknesses of various kinds of key-based template protection schemes. The goal is to provide the reader with a clear understanding of the current and emerging trends in key-based biometric cryptosystems.

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Section: Fuzzy Commitment Schemementioning

confidence: 99%

Section: Fuzzy Commitment Schemementioning

confidence: 99%

State of the Art in Biometric Key Binding and Key Generation Schemes

Jegede

Udzir

Abdullah

et al. 2022

Int. j. commun. netw. inf. secur.

View full text Add to dashboard Cite

show abstract

“…We showed in Table II the results of NIST STS Test Suite on the works [27], [30], [56], [35], [33], [36], [23] compared with MRE-IPI. The algorithms proposed in [30] and [31] are very similar and thus one column for their results is used for them.…”

Section: Test Suites Analysismentioning

confidence: 99%

Extracting Randomness from the Trend of IPI for Cryptographic Operations in Implantable Medical Devices

Chizari

Lupu

2021

IEEE Trans. Dependable and Secure Comput.

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Achieving secure communication between an Implantable Medical Device (IMD) inside the body and a gateway outside the body has showed its criticality with recent reports of hackings such as in St. Jude Medical's Implantable Cardiac Devices, Johnson and Johnson insulin pumps and vulnerabilities in brain Neuro-implants. The use of asymmetric cryptography in particular is not a practical solution for IMDs due to the scarce computational and power resources, symmetric key cryptography is preferred. One of the factors in security of a symmetric cryptographic system is to use a strong key for encryption. A solution to develop such a strong key without using extensive resources in an IMD, is to extract it from the body physiological signals. In order to have a strong enough key, the physiological signal must be a strong source of randomness and InterPulse Interval (IPI) has been advised to be such that. A strong randomness source should have five conditions: Universality (available on all people), Liveness (available at any-time), Robustness (strong random number), Permanence (independent from its history) and Uniqueness (independent from other sources). Nevertheless, for current proposed random extraction methods from IPI these conditions (mainly last three conditions) were not examined. In this study, firstly, we proposed a methodology to measure the last three conditions: Information secrecy measures for Robustness, Santha-Vazirani Source delta value for Permanence and random sources dependency analysis for Uniqueness. Then, using a huge dataset of IPI values (almost 900,000,000 IPIs), we showed that IPI does not have conditions of Robustness and Permanence as a randomness source. Thus, extraction of a strong uniform random number from IPI value, mathematically, is impossible. Thirdly, rather than using the value of IPI, we proposed the trend of IPI as a source for a new randomness extraction method named as Martingale Randomness Extraction from IPI (MRE-IPI). We evaluated MRE-IPI and showed that it satisfies the Robustness condition completely and Permanence to some level. Finally, we used NIST STS and Dieharder test suites and showed that MRE-IPI is able to outperform all recent randomness extraction methods from IPIs and its quality is half of the AES random number. MRE-IPI, still, is not a strong random number and could not be used as the secret key for a secure communication, however, it can be used as a one-time pad in exchanging the secret key for a communication. In this case, the usage of MRE-IPI will be kept at a minimum level and reduces the probability of breaking it. To the best of our knowledge, this is the first work in this area which uses such a comprehensive method and large dataset to examine the randomness of a physiological signal.

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A dynamic fuzzy commitment scheme using multiple commitments

Cited by 2 publications

References 2 publications

State of the Art in Biometric Key Binding and Key Generation Schemes

State of the Art in Biometric Key Binding and Key Generation Schemes

Extracting Randomness from the Trend of IPI for Cryptographic Operations in Implantable Medical Devices

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