6,866 research outputs found

    Formal Analysis of V2X Revocation Protocols

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    Research on vehicular networking (V2X) security has produced a range of security mechanisms and protocols tailored for this domain, addressing both security and privacy. Typically, the security analysis of these proposals has largely been informal. However, formal analysis can be used to expose flaws and ultimately provide a higher level of assurance in the protocols. This paper focusses on the formal analysis of a particular element of security mechanisms for V2X found in many proposals: the revocation of malicious or misbehaving vehicles from the V2X system by invalidating their credentials. This revocation needs to be performed in an unlinkable way for vehicle privacy even in the context of vehicles regularly changing their pseudonyms. The REWIRE scheme by Forster et al. and its subschemes BASIC and RTOKEN aim to solve this challenge by means of cryptographic solutions and trusted hardware. Formal analysis using the TAMARIN prover identifies two flaws with some of the functional correctness and authentication properties in these schemes. We then propose Obscure Token (OTOKEN), an extension of REWIRE to enable revocation in a privacy preserving manner. Our approach addresses the functional and authentication properties by introducing an additional key-pair, which offers a stronger and verifiable guarantee of successful revocation of vehicles without resolving the long-term identity. Moreover OTOKEN is the first V2X revocation protocol to be co-designed with a formal model.Comment: 16 pages, 4 figure

    SybMatch: Sybil detection for privacy-preserving task matching in crowdsourcing

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    The past decade has witnessed the rise of crowdsourcing, and privacy in crowdsourcing has also gained rising concern in the meantime. In this paper, we focus on the privacy leaks and sybil attacks during the task matching, and propose a privacy-preserving task matching scheme, called SybMatch. The SybMatch scheme can simultaneously protect the privacy of publishers and subscribers against semi-honest crowdsourcing service provider, and meanwhile support the sybil detection against greedy subscribers and efficient user revocation. Detailed security analysis and thorough performance evaluation show that the SybMatch scheme is secure and efficient

    Anonymous Attestation for IoT

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    Internet of Things (IoT) have seen tremendous growth and are being deployed pervasively in areas such as home, surveillance, health-care and transportation. These devices collect and process sensitive data with respect to user\u27s privacy. Protecting the privacy of the user is an essential aspect of security, and anonymous attestation of IoT devices are critical to enable privacy-preserving mechanisms. Enhanced Privacy ID (EPID) is an industry-standard cryptographic scheme that offers anonymous attestation. It is based on group signature scheme constructed from bilinear pairings, and provides anonymity and sophisticated revocation capabilities (private-key based revocation and signature-based revocation). Despite the interesting privacy-preserving features, EPID operations are very computational and memory intensive. In this paper, we present a small footprint anonymous attestation solution based on EPID that can meet the stringent resource requirements of IoT devices. A specific modular-reduction technique targeting the EPID prime number has been developed resulting in 50% latency reduction compared to conventional reduction techniques. Furthermore, we developed a multi-exponentiation technique that significantly reduces the runtime memory requirements. Our proposed design can be implemented as SW-only, or it can utilize an integrated Elliptic Curve and Galois Field HW accelerator. The EPID SW stack has a small object code footprint of 22kB. We developed a prototype on a 32-bit microcontroller that computes EPID signature generation in 17.9s at 32MHz

    An Efficient and Privacy-Preserving Multiuser Cloud-Based LBS Query Scheme

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    Location-based services (LBSs) are increasingly popular in today’s society. People reveal their location information to LBS providers to obtain personalized services such as map directions, restaurant recommendations, and taxi reservations. Usually, LBS providers offer user privacy protection statement to assure users that their private location information would not be given away. However, many LBSs run on third-party cloud infrastructures. It is challenging to guarantee user location privacy against curious cloud operators while still permitting users to query their own location information data. In this paper, we propose an efficient privacy-preserving cloud-based LBS query scheme for the multiuser setting. We encrypt LBS data and LBS queries with a hybrid encryption mechanism, which can efficiently implement privacy-preserving search over encrypted LBS data and is very suitable for the multiuser setting with secure and effective user enrollment and user revocation. This paper contains security analysis and performance experiments to demonstrate the privacy-preserving properties and efficiency of our proposed scheme

    A-MAKE: an efficient, anonymous and accountable authentication framework for WMNs

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    In this paper, we propose a framework, named as A-MAKE, which efficiently provides security, privacy, and accountability for communications in wireless mesh networks. More specifically, the framework provides an anonymous mutual authentication protocol whereby legitimate users can connect to network from anywhere without being identified or tracked. No single party (e.g., network operator) can violate the privacy of a user, which is provided in our framework in the strongest sense. Our framework utilizes group signatures, where the private key and the credentials of the users are generated through a secure three-party protocol. User accountability is implemented via user revocation protocol that can be executed by two semitrusted authorities, one of which is the network operator. The assumptions about the trust level of the network operator are relaxed. Our framework makes use of much more efficient signature generation and verification algorithms in terms of computation complexity than their counterparts in literature, where signature size is comparable to the shortest signatures proposed for similar purposes so far

    A Practical Set-Membership Proof for Privacy-Preserving NFC Mobile Ticketing

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    To ensure the privacy of users in transport systems, researchers are working on new protocols providing the best security guarantees while respecting functional requirements of transport operators. In this paper, we design a secure NFC m-ticketing protocol for public transport that preserves users' anonymity and prevents transport operators from tracing their customers' trips. To this end, we introduce a new practical set-membership proof that does not require provers nor verifiers (but in a specific scenario for verifiers) to perform pairing computations. It is therefore particularly suitable for our (ticketing) setting where provers hold SIM/UICC cards that do not support such costly computations. We also propose several optimizations of Boneh-Boyen type signature schemes, which are of independent interest, increasing their performance and efficiency during NFC transactions. Our m-ticketing protocol offers greater flexibility compared to previous solutions as it enables the post-payment and the off-line validation of m-tickets. By implementing a prototype using a standard NFC SIM card, we show that it fulfils the stringent functional requirement imposed by transport operators whilst using strong security parameters. In particular, a validation can be completed in 184.25 ms when the mobile is switched on, and in 266.52 ms when the mobile is switched off or its battery is flat

    Anonymous privacy-preserving task matching in crowdsourcing

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    With the development of sharing economy, crowdsourcing as a distributed computing paradigm has become increasingly pervasive. As one of indispensable services for most crowdsourcing applications, task matching has also been extensively explored. However, privacy issues are usually ignored during the task matching and few existing privacy-preserving crowdsourcing mechanisms can simultaneously protect both task privacy and worker privacy. This paper systematically analyzes the privacy leaks and potential threats in the task matching and proposes a single-keyword task matching scheme for the multirequester/multiworker crowdsourcing with efficient worker revocation. The proposed scheme not only protects data confidentiality and identity anonymity against the crowd-server, but also achieves query traceability against dishonest or revoked workers. Detailed privacy analysis and thorough performance evaluation show that the proposed scheme is secure and feasible
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