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.

In this correspondence, 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 (ACISP 2007), which is based on the Goldwasser-Micali cryptosystem, the related protocol of Barbosa (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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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 evaluate the power consumption of different digital signature schemes. We compare the cost of the elliptic curve digital signature algorithm with signature schemes solely based on symmetric techniques such as the Diffie-Lamport one-time signature scheme. These evaluations take into account all aspects of using digital signatures in wireless environments: energy consumption of key generation, signing and verification, and the communication cost of sending and receiving the necessary data (including the public keys and the necessary data to authenticate them).