This paper introduces an information theoretic model that allows to quantify the degree of anonymity provided by schemes for anonymous connections. It considers attackers that obtain probabilistic information about users. The degree is based on the probabilities an attacker, after observing the system, assigns to the different users of the system as being the originators of a message. As a proof of concept, the model is applied to some existing systems. The model is shown to be very useful for evaluating the level of privacy a system provides under various attack scenarios, for measuring the amount of information an attacker gets with a particular attack and for comparing different systems amongst each other.

Due to the nature of radio transmissions, communications in wireless networks are easy to capture and analyze. Next to this, privacy enhancing techniques (PETs) proposed for wired networks such as the Internet often cannot be applied to mobile ad hoc networks (MANETs). In this paper we present a novel anonymous on demand routing scheme for MANETs. We identify a number of problems of previously proposed works and propose an efficient solution that provides anonymity in a stronger adversary model.

In this paper we analyze the vulnerabilities of biometric authentication protocols with respect to user and data privacy. The goal of an adversary in such context is not to bypass the authentication but to learn information either on biometric data or on users that are in the system. We elaborate our analysis on a general system model involving four logical entities (sensor, server, database and matcher), and we focus on internal adversaries to encompass the situation where one or a combination of these entities would be malicious. Our goal is to emphasize that when going beyond the usual honest-but-curious assumption much more complex attacks can affect the privacy of data and users. On the one hand, we introduce a new comprehensive framework that encompasses the various schemes we want to look at. It presents a system model in which each internal entity or combination of entities is a potential attacker. Different attack goals are considered and resulting requirements on data flows are discussed. On the other hand, we develop different generic attacks. We follow a blackbox approach in which we consider components that perform operations on biometric data but where only the input/output behavior is analyzed. These attack strategies are exhibited on recent schemes such as the distributed protocol of Bringer et al. (ACISP 2007), which is based on the Goldwasser-Micali cryptosystem, the related protocol of Barbosa et al. (ACISP 2008), which uses the Paillier cryptosystem, and the scheme of Stoianov (SPIE 2010), that features the Blum-Goldwasser cryptosystem. All these schemes have been developed in the honest-but-curious adversary model and show potential weaknesses when considered in our malicious insider attack model.

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Since the introduction of the concept of grouping proofs by Juels, which permit RFID tags to generate evidence that they have been scanned simultaneously, various new schemes have been proposed. Their common property is the use of symmetric-key primitives. However, it has been shown that such schemes often entail scalability, security and/or privacy problems. In this article, we extend the notion of public-key RFID authentication protocols and propose a privacy-preserving multi-party grouping-proof protocol which relies exclusively on the use of elliptic curve cryptography (ECC). It allows to generate a proof which is verifiable by a trusted verifier in an offline setting, even when readers or tags are potentially untrusted, and it is privacy-preserving in the setting of a narrowstrong attacker. We also demonstrate that our RFID grouping-proof protocol can easily be extended to use cases with more than two tags, without any additional cost for an RFID tag. To illustrate the implementation feasibility of our proposed solutions, we present a novel ECC hardware architecture designed for RFID.