Evaluating On-demand Pseudonym Acquisition Policies in Vehicular Communication Systems

Standardization and harmonization efforts have reached a consensus towards using a special-purpose Vehicular Public-Key Infrastructure (VPKI) in upcoming Vehicular Communication (VC) systems. However, there are still several technical challenges with no conclusive answers; one such an important yet open challenge is the acquisition of shortterm credentials, pseudonym: how should each vehicle interact with the VPKI, e.g., how frequently and for how long? Should each vehicle itself determine the pseudonym lifetime? Answering these questions is far from trivial. Each choice can affect both the user privacy and the system performance and possibly, as a result, its security. In this paper, we make a novel systematic effort to address this multifaceted question. We craft three generally applicable policies and experimentally evaluate the VPKI system performance, leveraging two large-scale mobility datasets. We consider the most promising, in terms of efficiency, pseudonym acquisition policies; we find that within this class of policies, the most promising policy in terms of privacy protection can be supported with moderate overhead. Moreover, in all cases, this work is the first to provide tangible evidence that the state-of-the-art VPKI can serve sizable areas or domain with modest computing resources.Comment: 6 pages, 7 figures, IoV-VoI'1

Finger Vein Template Protection with Directional Bloom Filter

Biometrics has become a widely accepted solution for secure user authentication. However, the use of biometric traits raises serious concerns about the protection of personal data and privacy. Traditional biometric systems are vulnerable to attacks due to the storage of original biometric data in the system. Because biometric data cannot be changed once it has been compromised, the use of a biometric system is limited by the security of its template. To protect biometric templates, this paper proposes the use of directional bloom filters as a cancellable biometric approach to transform the biometric data into a non-invertible template for user authentication purposes. Recently, Bloom filter has been used for template protection due to its efficiency with small template size, alignment invariance, and irreversibility. Directional Bloom Filter improves on the original bloom filter. It generates hash vectors with directional subblocks rather than only a single-column subblock in the original bloom filter. Besides, we make use of multiple fingers to generate a biometric template, which is termed multi-instance biometrics. It helps to improve the performance of the method by providing more information through the use of multiple fingers. The proposed method is tested on three public datasets and achieves an equal error rate (EER) as low as 5.28% in the stolen or constant key scenario. Analysis shows that the proposed method meets the four properties of biometric template protection. Doi: 10.28991/HIJ-2023-04-02-013 Full Text: PD

Provably Unlinkable Smart Card-based Payments

The most prevalent smart card-based payment method, EMV, currently offers no privacy to its users. Transaction details and the card number are sent in cleartext, enabling the profiling and tracking of cardholders. Since public awareness of privacy issues is growing and legislation, such as GDPR, is emerging, we believe it is necessary to investigate the possibility of making payments anonymous and unlinkable without compromising essential security guarantees and functional properties of EMV. This paper draws attention to trade-offs between functional and privacy requirements in the design of such a protocol. We present the UTX protocol - an enhanced payment protocol satisfying such requirements, and we formally certify key security and privacy properties using techniques based on the applied pi-calculus

Cryptography for Bitcoin and friends

Numerous cryptographic extensions to Bitcoin have been proposed since Satoshi Nakamoto introduced the revolutionary design in 2008. However, only few proposals have been adopted in Bitcoin and other prevalent cryptocurrencies, whose resistance to fundamental changes has proven to grow with their success. In this dissertation, we introduce four cryptographic techniques that advance the functionality and privacy provided by Bitcoin and similar cryptocurrencies without requiring fundamental changes in their design: First, we realize smart contracts that disincentivize parties in distributed systems from making contradicting statements by penalizing such behavior by the loss of funds in a cryptocurrency. Second, we propose CoinShuffle++, a coin mixing protocol which improves the anonymity of cryptocurrency users by combining their transactions and thereby making it harder for observers to trace those transactions. The core of CoinShuffle++ is DiceMix, a novel and efficient protocol for broadcasting messages anonymously without the help of any trusted third-party anonymity proxies and in the presence of malicious participants. Third, we combine coin mixing with the existing idea to hide payment values in homomorphic commitments to obtain the ValueShuffle protocol, which enables us to overcome major obstacles to the practical deployment of coin mixing protocols. Fourth, we show how to prepare the aforementioned homomorphic commitments for a safe transition to post-quantum cryptography.Seit seiner revolutionären Erfindung durch Satoshi Nakamoto im Jahr 2008 wurden zahlreiche kryptographische Erweiterungen für Bitcoin vorgeschlagen. Gleichwohl wurden nur wenige Vorschläge in Bitcoin und andere weit verbreitete Kryptowährungen integriert, deren Resistenz gegen tiefgreifende Veränderungen augenscheinlich mit ihrer Verbreitung wächst. In dieser Dissertation schlagen wir vier kryptographische Verfahren vor, die die Funktionalität und die Datenschutzeigenschaften von Bitcoin und ähnlichen Kryptowährungen verbessern ohne deren Funktionsweise tiefgreifend verändern zu müssen. Erstens realisieren wir Smart Contracts, die es erlauben widersprüchliche Aussagen einer Vertragspartei mit dem Verlust von Kryptogeld zu bestrafen. Zweitens schlagen wir CoinShuffle++ vor, ein Mix-Protokoll, das die Anonymität von Benutzern verbessert, indem es ihre Transaktionen kombiniert und so deren Rückverfolgung erschwert. Sein Herzstück ist DiceMix, ein neues und effizientes Protokoll zur anonymen Veröffentlichung von Nachrichten ohne vertrauenswürdige Dritte und in der Präsenz von bösartigen Teilnehmern. Drittens kombinieren wir dieses Protokoll mit der existierenden Idee, Geldbeträge in Commitments zu verbergen, und erhalten so das ValueShuffle-Protokoll, das uns ermöglicht, große Hindernisse für den praktischen Einsatz von Mix-Protokollen zu überwinden. Viertens zeigen wir, wie die dabei benutzten Commitments für einen sicheren Übergang zu Post-Quanten-Kryptographie vorbereitet werden können

Hang With Your Buddies to Resist Intersection Attacks

Some anonymity schemes might in principle protect users from pervasive network surveillance - but only if all messages are independent and unlinkable. Users in practice often need pseudonymity - sending messages intentionally linkable to each other but not to the sender - but pseudonymity in dynamic networks exposes users to intersection attacks. We present Buddies, the first systematic design for intersection attack resistance in practical anonymity systems. Buddies groups users dynamically into buddy sets, controlling message transmission to make buddies within a set behaviorally indistinguishable under traffic analysis. To manage the inevitable tradeoffs between anonymity guarantees and communication responsiveness, Buddies enables users to select independent attack mitigation policies for each pseudonym. Using trace-based simulations and a working prototype, we find that Buddies can guarantee non-trivial anonymity set sizes in realistic chat/microblogging scenarios, for both short-lived and long-lived pseudonyms.Comment: 15 pages, 8 figure

A Privacy Preserving Distributed Reputation Mechanism

International audienceReputation systems allow to estimate the trustworthiness of entities based on their past behavior. Electronic commerce, peer-to-peer routing and collaborative environments, just to cite a few, highly benefit from using reputation systems. To guarantee an accurate estimation, reputation systems typically rely on a central authority, on the identification and authentication of all the participants, or both. In this paper, we go a step further by presenting a distributed reputation mechanism which is robust against malicious behaviors and that preserves the privacy of its clients. Guaranteed error bounds on the estimation are provided