1,440 research outputs found

    Key-Homomorphic Signatures: Definitions and Applications to Multiparty Signatures and Non-Interactive Zero-Knowledge

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    Key-homomorphic properties of cryptographic objects, i.e., homomorphisms on their key space, have proven to be useful, both from a theoretical as well as a practical perspective. Important cryptographic objects such as pseudorandom functions or (public key) encryption have been studied previously with respect to key-homomorphisms. Interestingly, however, signature schemes have not been explicitly investigated in this context so far. We close this gap and initiate the study of key-homomorphic signatures, which turns out to be an interesting and versatile concept. In doing so, we firstly propose a definitional framework for key-homomorphic signatures distilling various natural flavours of key-homomorphic properties. Those properties aim to classify existing signature schemes and thus allow to infer general statements about signature schemes from those classes by simply making black-box use of the respective properties. We apply our definitional framework to show elegant and simple compilers from classes of signature schemes admitting different types of key-homomorphisms to a number of other interesting primitives such as ring signature schemes, (universal) designated verifier signature schemes, simulation-sound extractable non-interactive zero-knowledge (NIZK) arguments, and multisignature schemes. Additionally, using the formalisms provided by our framework, we can prove a tight implication from single-user security to key-prefixed multi-user security for a class of schemes admitting a certain key-homomorphism. Finally, we discuss schemes that provide homomorphic properties on the message space of signatures under different keys in context of key-homomorphisms and present some first constructive results from key-homomorphic schemes

    A New Cryptosystem Based On Hidden Order Groups

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    Let G1G_1 be a cyclic multiplicative group of order nn. It is known that the Diffie-Hellman problem is random self-reducible in G1G_1 with respect to a fixed generator gg if ϕ(n)\phi(n) is known. That is, given g,gx∈G1g, g^x\in G_1 and having oracle access to a `Diffie-Hellman Problem' solver with fixed generator gg, it is possible to compute g1/x∈G1g^{1/x} \in G_1 in polynomial time (see theorem 3.2). On the other hand, it is not known if such a reduction exists when ϕ(n)\phi(n) is unknown (see conjuncture 3.1). We exploit this ``gap'' to construct a cryptosystem based on hidden order groups and present a practical implementation of a novel cryptographic primitive called an \emph{Oracle Strong Associative One-Way Function} (O-SAOWF). O-SAOWFs have applications in multiparty protocols. We demonstrate this by presenting a key agreement protocol for dynamic ad-hoc groups.Comment: removed examples for multiparty key agreement and join protocols, since they are redundan

    Revealing the Landscape of Privacy-Enhancing Technologies in the Context of Data Markets for the IoT: A Systematic Literature Review

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    IoT data markets in public and private institutions have become increasingly relevant in recent years because of their potential to improve data availability and unlock new business models. However, exchanging data in markets bears considerable challenges related to disclosing sensitive information. Despite considerable research focused on different aspects of privacy-enhancing data markets for the IoT, none of the solutions proposed so far seems to find a practical adoption. Thus, this study aims to organize the state-of-the-art solutions, analyze and scope the technologies that have been suggested in this context, and structure the remaining challenges to determine areas where future research is required. To accomplish this goal, we conducted a systematic literature review on privacy enhancement in data markets for the IoT, covering 50 publications dated up to July 2020, and provided updates with 24 publications dated up to May 2022. Our results indicate that most research in this area has emerged only recently, and no IoT data market architecture has established itself as canonical. Existing solutions frequently lack the required combination of anonymization and secure computation technologies. Furthermore, there is no consensus on the appropriate use of blockchain technology for IoT data markets and a low degree of leveraging existing libraries or reusing generic data market architectures. We also identified significant challenges remaining, such as the copy problem and the recursive enforcement problem that-while solutions have been suggested to some extent-are often not sufficiently addressed in proposed designs. We conclude that privacy-enhancing technologies need further improvements to positively impact data markets so that, ultimately, the value of data is preserved through data scarcity and users' privacy and businesses-critical information are protected.Comment: 49 pages, 17 figures, 11 table

    Distributed Protocols at the Rescue for Trustworthy Online Voting

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    While online services emerge in all areas of life, the voting procedure in many democracies remains paper-based as the security of current online voting technology is highly disputed. We address the issue of trustworthy online voting protocols and recall therefore their security concepts with its trust assumptions. Inspired by the Bitcoin protocol, the prospects of distributed online voting protocols are analysed. No trusted authority is assumed to ensure ballot secrecy. Further, the integrity of the voting is enforced by all voters themselves and without a weakest link, the protocol becomes more robust. We introduce a taxonomy of notions of distribution in online voting protocols that we apply on selected online voting protocols. Accordingly, blockchain-based protocols seem to be promising for online voting due to their similarity with paper-based protocols

    Private Multi-party Matrix Multiplication and Trust Computations

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    This paper deals with distributed matrix multiplication. Each player owns only one row of both matrices and wishes to learn about one distinct row of the product matrix, without revealing its input to the other players. We first improve on a weighted average protocol, in order to securely compute a dot-product with a quadratic volume of communications and linear number of rounds. We also propose a protocol with five communication rounds, using a Paillier-like underlying homomorphic public key cryptosystem, which is secure in the semi-honest model or secure with high probability in the malicious adversary model. Using ProVerif, a cryptographic protocol verification tool, we are able to check the security of the protocol and provide a countermeasure for each attack found by the tool. We also give a randomization method to avoid collusion attacks. As an application, we show that this protocol enables a distributed and secure evaluation of trust relationships in a network, for a large class of trust evaluation schemes.Comment: Pierangela Samarati. SECRYPT 2016 : 13th International Conference on Security and Cryptography, Lisbonne, Portugal, 26--28 Juillet 2016. 201
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