1,563 research outputs found

    SPATA: Strong Pseudonym based AuthenTicAtion in Intelligent Transport System

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    Intelligent Transport System (ITS) is generally deployed to improve road safety, comfort, security, and traffic efficiency. A robust mechanism of authentication and secure communication is required to protect privacy and conditional resolution of pseudonyms to revoke malicious vehicles. In a typical ITS framework, a station can be a vehicle, Road Side Unit (RSU), or a server that can participate in communication. During authentication, the real identity of an Intelligent Transport System-Station (ITSS), referred to as a vehiclečƈ should not be revealed in order to preserve its privacy. In this paper, we propose a Strong Pseudonym based AutenTicAtion (SPATA) framework for preserving the real identity of vehicles. The distributed architecture of SPATA allows vehicles to generate pseudonyms in a very private and secure way. In the absence of a distributed architecture, the privacy cannot be preserved by storing information regarding vehicles in a single location. Therefore, the concept of linkability of certificates based on single authority is eliminated. This is done by keeping the real identity to pseudonym mappings distributed. Furthermore, the size of the Certificate Revocation List (CRL) is kept small, as only the most recent revoked communication pseudonyms are kept in the CRL. The privacy of the vehicle is preserved during the revocation and resolution phase through the distributed mechanism. Empirical results show that SPATA is a lightweight framework with low computational overhead, average latency, overhead ratio, and stable delivery ratio, in both sparse and dense network scenarios

    Signature Schemes with Efficient Protocols and Dynamic Group Signatures from Lattice Assumptions

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    International audienceA recent line of works – initiated by Gordon, Katz and Vaikuntanathan (Asiacrypt 2010) – gave lattice-based realizations of privacy-preserving protocols allowing users to authenticate while remaining hidden in a crowd. Despite five years of efforts, known constructions remain limited to static populations of users, which cannot be dynamically updated. For example, none of the existing lattice-based group signatures seems easily extendable to the more realistic setting of dynamic groups. This work provides new tools enabling the design of anonymous authen-tication systems whereby new users can register and obtain credentials at any time. Our first contribution is a signature scheme with efficient protocols, which allows users to obtain a signature on a committed value and subsequently prove knowledge of a signature on a committed message. This construction, which builds on the lattice-based signature of Böhl et al. (Eurocrypt'13), is well-suited to the design of anonymous credentials and dynamic group signatures. As a second technical contribution, we provide a simple, round-optimal joining mechanism for introducing new members in a group. This mechanism consists of zero-knowledge arguments allowing registered group members to prove knowledge of a secret short vector of which the corresponding public syndrome was certified by the group manager. This method provides similar advantages to those of structure-preserving signatures in the realm of bilinear groups. Namely, it allows group members to generate their public key on their own without having to prove knowledge of the underlying secret key. This results in a two-round join protocol supporting concurrent enrollments, which can be used in other settings such as group encryption

    A Geometric Variational Approach to Bayesian Inference

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    We propose a novel Riemannian geometric framework for variational inference in Bayesian models based on the nonparametric Fisher-Rao metric on the manifold of probability density functions. Under the square-root density representation, the manifold can be identified with the positive orthant of the unit hypersphere in L2, and the Fisher-Rao metric reduces to the standard L2 metric. Exploiting such a Riemannian structure, we formulate the task of approximating the posterior distribution as a variational problem on the hypersphere based on the alpha-divergence. This provides a tighter lower bound on the marginal distribution when compared to, and a corresponding upper bound unavailable with, approaches based on the Kullback-Leibler divergence. We propose a novel gradient-based algorithm for the variational problem based on Frechet derivative operators motivated by the geometry of the Hilbert sphere, and examine its properties. Through simulations and real-data applications, we demonstrate the utility of the proposed geometric framework and algorithm on several Bayesian models

    A VANET privacy protection scheme based on fair blind signature and secret sharing algorithm

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    Vehicular ad hoc network (VANET) is a traffic application of wireless sensor network, which is also a new mobile ad hoc networks composed of vehicle nodes, roadside units, service providers and other components. In VANET, data is transmitted by the wireless channel, which is subject to potential threat like information leak and data attack due to the openness and sensitivity of the auto organization network itself. How to ensure the identity privacy and trusted communication in VANETs is the key issue to be solved urgently. The existing work usually uses authentication mechanism, but the user’s privacy disclosure is inevitable during the authentication process. Some anonymous authentication schemes have been proposed to solve the problem of privacy disclosure regardless of considering anonymity abuse. However, anonymity abuse is also severe in VANET. In view of the above problems, this paper proposes a scheme based on fair blind signature and secret sharing algorithm. By security analysis and experiment, the scheme has been proved to be higher anonymity and higher efficiency

    SoK: Secure E-Voting with Everlasting Privacy

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    Vote privacy is a fundamental right, which needs to be protected not only during an election, or for a limited time afterwards, but for the foreseeable future. Numerous electronic voting (e-voting) protocols have been proposed to address this challenge, striving for everlasting privacy. This property guarantees that even computationally unbounded adversaries cannot break privacy of past elections. The broad interest in secure e-voting with everlasting privacy has spawned a large variety of protocols over the last three decades. These protocols differ in many aspects, in particular the precise security properties they aim for, the threat scenarios they consider, and the privacy-preserving techniques they employ. Unfortunately, these differences are often opaque, making analysis and comparison cumbersome. In order to overcome this non-transparent state of affairs, we systematically analyze all e-voting protocols designed to provide everlasting privacy. First, we illustrate the relations and dependencies between all these different protocols. Next, we analyze in depth which protocols do provide secure and efficient approaches to e-voting with everlasting privacy under realistic assumptions, and which ones do not. Eventually, based on our extensive and detailed treatment, we identify which research problems in this field have already been solved, and which ones are still open. Altogether, our work offers a well-founded reference point for conducting research on secure e-voting with everlasting privacy as well as for future-proofing privacy in real-world electronic elections

    Randomness invalidates criminal smart contracts

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    A smart contract enforces specific performance on anonymous users without centralization. It facilitates payment equity in commerce by providing irreversible transactions. Smart contracts are also used for illegal activities such as money laundering and ransomware. Such contracts include criminal smart contracts (CSCs), proposed in CCS’16, that can be efficiently implemented in existing scripting languages. This aggravates concerns about the dangers of CSCs. However, PublicLeaks, a CSC for leaking private data, is conditionally implemented as it is influenced by various factors. For example, PublicLeaks does not necessarily reach a desirable terminal state for a criminal leaking private information, and other possible terminal states may invalidate the CSC. In this study, we propose a CSC based on PublicLeaks by formulating random factors such as the donation ratio. Our contract forks into five terminal states, including a unique one in PublicLeaks due to randomness. We simulated the maximal probabilities of these terminal states and found that the desirable terminal state in PublicLeaks is reachable with low probabilities (lower than 25%). The terminal state where the criminal fails to leak private information is attained with relatively high probabilities (over 65%). Therefore, our simulations show that CSCs are not always as powerful as expected, and the risk posed by them can be mitigated
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