A Reusable Fuzzy Extractor with Practical Storage Size: Modifying Canetti et al.’s Construction

Cheon, Jung Hee; Jeong, Jinhyuck; Kim, Dongwoo; Lee, Jong-Chan

doi:10.1007/978-3-319-93638-3_3

Cited by 21 publications

(19 citation statements)

References 20 publications

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“…Recently, several reusable fuzzy extractor schemes have been introduced [32], [34]- [36]. In [34]- [36], the size of the helper data has been reduced compared to [1], but they are not capable of handling the outliers in the user's fuzzy data.…”

Section: Discussionmentioning

confidence: 99%

“…In [34]- [36], the size of the helper data has been reduced compared to [1], but they are not capable of handling the outliers in the user's fuzzy data. In [32], Cheon et al have modified the reusable fuzzy extractor proposed in [1] and reduced the size of helper data by adopting a threshold scheme. However, this scheme still requires much more storage space as compared to ours.…”

Section: Discussionmentioning

confidence: 99%

“…At the 80-bit security level, |G 1 | is 171-bit [33], and the size of helper data in our FVS scheme is (3n + 1)|G 1 |. As for the scheme of [32], the parameters shown in Table 2 of [32] are used as such.…”

Section: Discussionmentioning

confidence: 99%

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Fuzzy Vector Signature and Its Application to Privacy-Preserving Authentication

et al. 2019

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Fuzzy authentication uses non-deterministic or noisy data, like biometrics, as an authentication factor. Although the data is extracted from the same individual or source, it can be different for each measurement. As a result, one of the main issues in fuzzy authentication is the effective processing of the fuzziness, while guaranteeing the privacy of the fuzzy data. Biometric data is a typical user-generated fuzzy data and the fuzzy extractor is one of the most promising primitives for biometric authentication these days. In 2016, Canetti et al. proposed the reusable fuzzy extractor, in which multiple keys can be generated with the same biometric data. It can also handle some outliers which occur unexpectedly (owing to an external interference when acquiring the fuzzy data, for example, the presence of dust on a fingerprint image). However, the size of the user's helper data in the reusable fuzzy extractor is quite large. This makes the network bandwidth usage required in the online authentication phase (or the storage required on the user side) considerable, which inconveniences the user. In this paper, we present a new primitive for fuzzy authentication, called a fuzzy vector signature (FVS) scheme, which significantly alleviates the burden on the user side. This means that the network bandwidth usage (or the amount of storage required on the user side) is significantly reduced. The proposed FVS scheme is reusable and robust to outliers as well. Finally, we provide a privacy-preserving fuzzy authentication protocol based on the FVS scheme.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Fuzzy Vector Signature and Its Application to Privacy-Preserving Authentication

et al. 2019

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“…and Rep(.) functions at least stored in 1024‐bit memory [29]. Therefore, comparison of the storage overhead of the proposed scheme with [20, 23, 30, 31] is shown in Table 1.…”

Section: Performance Analysismentioning

confidence: 99%

Mitigating the desynchronisation attack in multiserver environment

Jan

Qayum

2020

IET Communications

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“…• Rep is a ''deterministic algorithm'' that recovers biometric secret key b i ∈ M from inputted noisy biometrics BIO i and reproduction parameter τ i as b i = Rep(BIO i , τ i ) provided that the Hamming distance between the original biometrics BIO i and current biometrics BIO i does not exceed a pre-defined error tolerance threshold value, say et. An estimate on error tolerance threshold values is given by Cheon et al [35] as follows. If the Hamming distance between the original biometrics BIO i and current biometrics BIO i is HD and the number of bits in input string is b, then et = HD b .…”

Section: B Fuzzy Extractormentioning

confidence: 99%

A Dynamic Privacy-Preserving Key Management Protocol for V2G in Social Internet of Things

Park

Das

et al. 2019

IEEE Access

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With the smart grid (SG) and the social Internet of Things (SIoT), an electric vehicle operator can use reliable, flexible, and efficient charging service with vehicle-to-grid (V2G). However, open channels can be vulnerable to various attacks by a malicious adversary. Therefore, secure mutual authentication for V2G has become essential, and numerous related protocols have been proposed. In 2018, Shen et al. proposed a privacy-preserving and lightweight key agreement protocol for V2G in SIoT to ensure security. However, we demonstrate that their protocol does not withstand impersonation, privileged-insider, and offline password guessing attacks, and it does not also guarantee secure mutual authentication, session key security, and perfect forward secrecy. Therefore, this paper proposes a dynamic privacy-preserving and lightweight key agreement protocol for V2G in SIoT to resolve the security weaknesses of Shen et al.'s protocol. The proposed protocol resists several attacks including impersonation, offline password guessing, man-in-the-middle, replay, and trace attacks, ensures anonymity, perfect forward secrecy, session key security, and secure mutual authentication. We evaluate the security of the proposed protocol using formal security analysis under the broadly-accepted real-or-random (ROR) model, secure mutual authentication proof using the widely-accepted Burrows-Abadi-Needham (BAN) logic, informal (non-mathematical) security analysis, and also the formal security verification using the broadly-accepted automated validation of Internet security protocols and applications (AVISPA) tool. We then compare computation costs, and security and functionality features of the proposed protocol with related protocols. Overall, the proposed protocol provides superior security, and it can be efficiently deployed to practical SIoT-based V2G environment. INDEX TERMS Social Internet of Things (SIoT), vehicle-to-grid (V2G), authentication, AVISPA, formal security, key management.

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A Reusable Fuzzy Extractor with Practical Storage Size: Modifying Canetti et al.’s Construction

Cited by 21 publications

References 20 publications

Fuzzy Vector Signature and Its Application to Privacy-Preserving Authentication

Fuzzy Vector Signature and Its Application to Privacy-Preserving Authentication

Mitigating the desynchronisation attack in multiserver environment

A Dynamic Privacy-Preserving Key Management Protocol for V2G in Social Internet of Things

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