Andreas Put

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 retailers 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.

PriMan: Facilitating the Development of Secure and Privacy-Preserving Applications

Security and privacy are essential in today’s information-driven society. However, security technologies and privacy-enhancing technologies (PETs) are often difficult to integrate in applications due to their inherent complexity and steep learning curve. In this paper, we present a flexible, technology agnostic development framework that facilitates the integration of security and privacy-preserving technologies into applications. Technology-specific configuration details are shifted from the application code to configuration policies. These policies are configured by domain experts independently from the application’s source code. We developed a prototype in Java, called PriMan, which runs on both desktops and Android based devices. Our experimental evaluation demonstrates that PriMan introduces a low and acceptable overhead (e.g., less than one millisecond per operation). In addition, we compare PriMan with other, freely available solutions. PriMan facilitates the integration of PETs and security technologies in current and future applications.

PACCo: Privacy-friendly Access Control with Context

We propose a secure and privacy friendly way to strengthen authentication mechanisms of online services by taking context into account. The use of context, however, is often of a personal nature (e.g. location) and introduces privacy risks. Furthermore, some context sources can be spoofed, and hence, the level of trust of a verifier in a context source can vary. In this paper, a policy language to express contextual constraints is proposed. In addition, a set of protocols to gather, verify and use contextual information in access control decisions is described. The system protects user privacy as service providers do not learn precise context information, and avoids linkabilities. Finally, we have implemented this system and our experimental evaluation shows that it is practical to use.

EmailCloak: A Practical and Flexible Approach to Improve Email Privacy

Millions of users rely on email providers to manage and store their personal communications. This vast amount of private information, however, is often misused not only by adversaries, but also by the providers themselves. End-to-end email encryption is considered the most robust defense against this threat, however, its many requirements make this approach impractical for protecting everyday emails. In this paper, we present Email Cloak, an email alias service with public key encryption capabilities. Email Cloak relaxes email encryption requirements by relying on a privacy-respecting third-party. Emails sent and received by the user are automatically encrypted with her public key by Email Cloak before being forwarded to, and stored by her email provider. This approach, while seemingly straightforward, offers multiple benefits: simplified key management, selective and automatic encryption, advanced deployment options and transparency towards other parties. Moreover, our experimental evaluation shows that the overhead introduced by Email Cloak is adequate for email communications. We have also made our implementation publicly available. In doing so, we deliver a practical and flexible tool that provides privacy-concerned users with greater control over their stored emails.

Attribute-Based Privacy-Friendly Access Control with Context

In the last decade, the Internet landscape transformed into a service platform. This evolution has brought more importance to security requirements like strong authentication. We propose a secure and privacy-friendly way to augment authentication mechanisms of Online services by taking context into account. Contextual information, such as location, proximity or the current role of a user in a system is useful to help authenticate and authorize users. Context, however, is often of a personal nature and introduces privacy risks. In addition, a source of such contextual information should provide trustworthy information.

An Efficient, Anonymous and Unlinkable Incentives Scheme

Incentives systems, such as loyalty schemes or reputation systems, are a popular way to encourage user actions or build a user-service provider relationship. In this paper, the authors describe uCentive, a privacy-preserving incentives scheme that allows users to earn and redeem incentives that cannot be linked to their identities or actions. In addition, users can prove ownership of their incentives without breaking unlinkability guarantees. uCentive also supports forward unlinkability-even if the users secrets are compromised, they cannot be linked to previous users actions.

An Advanced, Privacy-Friendly Loyalty System

Loyalty systems are a very popular service employed by retailers in order to measure and reward customer loyalty. However, currently deployed systems introduce many privacy risks, as the users’ data is completely controlled by retailers. In this work we tackle this issue by investigating the requirements posed on a privacy-friendly loyalty system and proposing a new design for a digital loyalty system. With this novel approach, the users are given more control over their data, but retailers are still able to measure their loyalty and perform (authorised) data collection. Additionally, the functionality of the design is flexible and allows for deployment of more advanced services.