InShopnito: an advanced yet privacy-friendly mobile shopping application

Mobile Shopping Applications (MSAs) are rapidly gaining popularity. They enhance the shopping experience, by offering customized recommendations or incorporating customer loyalty programs. Although MSAs are quite effective at attracting new customers and binding existing ones to a retailer's services, existing MSAs have several shortcomings. The data collection practices involved in MSAs and the lack of transparency thereof are important concerns for many customers. This paper presents inShopnito, a privacy-preserving mobile shopping application. All transactions made in inShopnito are unlinkable and anonymous. However, the system still offers the expected features from a modern MSA. Customers can take part in loyalty programs and earn or spend loyalty points and electronic vouchers. Furthermore, the MSA can suggest personalized recommendations even though the retailer cannot construct rich customer profiles. These profiles are managed on the smartphone and can be partially disclosed in order to get better, customized recommendations. Finally, we present an implementation called inShopnito, of which the security and performance is analyzed. In doing so, we show that it is possible to have a privacy-preserving MSA without having to sacrifice practicality

Anonymity and Rewards in Peer Rating Systems

When peers rate each other, they may choose to rate inaccurately in order to boost their own reputation or unfairly lower another’s. This could be successfully mitigated by having a reputation server incentivise accurate ratings with a reward. However, assigning rewards becomes a challenge when ratings are anonymous, since the reputation server cannot tell which peers to reward for rating accurately. To address this, we propose an anonymous peer rating system in which users can be rewarded for accurate ratings, and we formally define its model and security requirements. In our system ratings are rewarded in batches, so that users claiming their rewards only reveal they authored one in this batch of ratings. To ensure the anonymity set of rewarded users is not reduced, we also split the reputation server into two entities, the Rewarder, who knows which ratings are rewarded, and the Reputation Holder, who knows which users were rewarded. We give a provably secure construction satisfying all the security properties required. For our construction we use a modification of a Direct Anonymous Attestation scheme to ensure that peers can prove their own reputation when rating others, and that multiple feedback on the same subject can be detected. We then use Linkable Ring Signatures to enable peers to be rewarded for their accurate ratings, while still ensuring that ratings are anonymous. Our work results in a system which allows for accurate ratings to be rewarded, whilst still providing anonymity of ratings with respect to the central entities managing the system

Providing Efficient Privacy-Aware Incentives for Mobile Sensing

Abstract—Mobile sensing relies on data contributed by users through their mobile device (e.g., smart phone) to obtain useful information about people and their surroundings. However, users may not want to contribute due to lack of incentives and concerns on possible privacy leakage. To effectively promote user participation, both incentive and privacy issues should be addressed. Existing work on privacy-aware incentive is limited to special scenario of mobile sensing where each sensing task needs only one data report from each user, and thus not appropriate for generic scenarios in which sensing tasks may require multiple reports from each user (e.g., in environmental monitoring applications). In this paper, we propose a privacy-aware incentive scheme for general mobile sensing, which allows each sensing task to collect one or multiple reports from each user as needed. Besides being more flexible in task management, our scheme has much lower computation and communication cost compared to the existing solution. Evaluations show that, when each node only contributes data for a small fraction of sensing tasks (e.g, due to the incapability or disqualification to generate sensing data for other tasks), our scheme runs at least one order of magnitude faster. I

RHyTHM: A Randomized Hybrid Scheme To Hide in the Mobile Crowd

Any on-demand pseudonym acquisition strategy is problematic should the connectivity to the credential management infrastructure be intermittent. If a vehicle runs out of pseudonyms with no connectivity to refill its pseudonym pool, one solution is the on-the-fly generation of pseudonyms, e.g., leveraging anonymous authentication. However, such a vehicle would stand out in the crowd: one can simply distinguish pseudonyms, thus signed messages, based on the pseudonym issuer signature, link them and track the vehicle. To address this challenge, we propose a randomized hybrid scheme, RHyTHM, to enable vehicles to remain operational when disconnected without compromising privacy: vehicles with valid pseudonyms help others to enhance their privacy by randomly joining them in using on-the-fly self-certified pseudonyms along with aligned lifetimes. This way, the privacy of disconnected users is enhanced with a reasonable computational overhead.Comment: 4 pages, 4 figures, IEEE Vehicular Networking Conference (VNC), November 27-29, 2017, Torino, Ital

PPAA: Peer-to-Peer Anonymous Authentication (Extended Version)

In the pursuit of authentication schemes that balance user privacy and accountability, numerous anonymous credential systems have been constructed. However, existing systems assume a client-server architecture in which only the clients, but not the servers, care about their privacy. In peer-to-peer (P2P) systems where both clients and servers are peer users with privacy concerns, no existing system correctly strikes that balance between privacy and accountability. In this paper, we provide this missing piece: a credential system in which peers are {\em pseudonymous} to one another (that is, two who interact more than once can recognize each other via pseudonyms) but are otherwise anonymous and unlinkable across different peers. Such a credential system finds applications in, e.g., Vehicular Ad-hoc Networks (VANets) and P2P networks. We formalize the security requirements of our proposed credential system, provide a construction for it, and prove the security of our construction. Our solution is efficient: its complexities are independent of the number of users in the system

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