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Efficient biometric-based identity management on the Blockchain for smart industrial applications
مدیریت هویت مبتنی بر بیومتریک کارآمد در Blockchain برای کاربردهای صنعتی هوشمند-2021 In this work, we propose a new Blockchain-based Identity Management system for smart industry. First, we describe an efficient biometric-based anonymous credential scheme, which supports selective disclosure, suspension/thaw and revocation of credentials/entities. Our system provides non-transferability through a freshly computed hidden biometric attribute, which is generated using a secure fuzzy extractor during each authentication. This mechanism combined with offchain storage guarantees GDPR compliance, which is required for protecting user’s data. We define blinded (Brands) DLRep scheme to provide multi-show unlinkability, which is a lacking feature in Brands’ credential based systems. For larger organizations, we re-design the system by replacing the Merkle Tree with an accumulator to improve scalability. The new system enables auditing by adapting the standard Industrial IoT (IIoT) Identity Management Lifecycle to Blockchain. Finally, we show that the new proposal outperforms BASS, i.e. the most recent blockchain-based anonymous credential scheme designed for smart industry. The computational cost at the user-side (can be a weak IoT device) of our scheme is 8-times less than that of BASS. Thus, our system is more suitable for IIoT.© 2020 Elsevier B.V. All rights reserved. Keywords: Identity management | Smart industry | Blockchain | Non-transferability | Biometrics | DLRep | Multi-show unlinkability | Selective disclosure | Accumulators |
مقاله انگلیسی |
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Comments on biometric-based non-transferable credentials and their application in blockchain-based identity management
نظرات در مورد اعتبارنامه های غیرقابل انتقال مبتنی بر بیومتریک و کاربرد آنها در مدیریت هویت مبتنی بر بلاک چین-2021 In IT-ecosystems, access to unauthorized parties is prevented with credential-based access control techniques (locks, RFID cards, biometrics, etc.). Some of these methods are
ineffective against malicious users who lend their credentials to other users. To obtain
non-transferability, Adams proposed a combination of biometrics encapsulated in Pedersen
commitment with Brands digital credential. However, Adams’ work does not consider the
Zero Knowledge Proof-of Knowledge (ZKPoK) system for Double Discrete Logarithm Representation of the credential. Besides, biometrics is used directly, without employing any
biometric cryptosystem to guarantee biometric privacy, thus Adams’ work cannot be GDP compliant. In this paper, we construct the missing ZKPoK protocol for Adam’s work and
show its inefficiency. To overcome this limitation, we present a new biometric-based nontransferable credential scheme that maintains the efficiency of the underlying Brands credential. Secondly, we show the insecurity of the first biometric-based anonymous credential
scheme designed by Blanton et al.. In this context, we present a brute-force attack against
Blanton’s biometric key generation algorithm implemented for fuzzy vault. Next, we integrate an Oblivious PRF (OPRF) protocol to solve the open problem in Blanton’s work and
improve its efficiency by replacing the underlying signature scheme with PS-signatures. Finally, we evaluate application scenarios for non-transferable digital/anonymous credentials
in the context of Blockchain-based Identity Management (BBIM). We show that our modified constructions preserve biometric privacy and efficiency, and can easily be integrated
into current BBIM systems built upon efficient Brands and PS-credentials. Keywords: Biometrics security | Non-transferability | Digital credentials | Anonymous credentials | Fuzzy vault | Fuzzy extractors | Double discrete logarithm (DDL) | Brands DLRep | Selective disclosure | Blockchain | Identity management |
مقاله انگلیسی |