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Authors: Constantinos Patsakis, Agusti Solanas.

Publication date: 2013/12/19

Journal: IEEE Communications Magazine

Description: Vehicles are equipped with more technology with each passing day. Acronyms such as ABS (anti-lock braking system), EBD (electronic brakeforce distribution) or EPS (electric power steering) have become commonplace, and are used as synonyms for safety and comfort. On the contrary, others like EDR (event data recorder) are not as popular. EDR, commonly known as automotive black boxes, are devices used to col- lect data about a vehicle and its occupants, which can be accessed after an accident to clarify its cause. With the upcoming regulation of the National Highway Traffic Safety Administration requiring manufacturers to include EDR in all new vehicles, privacy advocates have raised some alarms related to the storage of and access to these data. In this article, we propose a novel privacy-aware solution for the EDR of modern vehicles. Our solution is based on modern cryp- tographic primitives like timed release encryp- tion (TRE), and it guarantees the privacy of the vehicle’s occupants while allowing the full func- tionality of EDR in case of emergency.

Authors: Athanasios Zigomitros, Fran Casino, Agusti Solanas, Constantinos Patsakis.

Publication date: 2020/3/11

Journal: IEEE Access

Description: Recent advances in telecommunications and database systems have allowed the scientific community to efficiently mine vast amounts of information worldwide and to extract new knowledge by discovering hidden patterns and correlations. Nevertheless, all this shared information can be used to invade the privacy of individuals through the use of fusion and mining techniques. Simply removing direct identifiers such as name, SSN, or phone number is not anymore sufficient to prevent against these practices. In numerous cases, other fields, like gender, date of birth and/or zipcode, can be used to re-identify individuals and to expose their sensitive details, e.g. their medical conditions, financial statuses and transactions, or even their private connections. The scope of this work is to provide an in-depth overview of the current state of the art in Privacy-Preserving Data Publishing (PPDP) for relational data. To counter information leakage, a number of data anonymisation methods have been proposed during the past few years, including k-anonymity, l-diversity, t-closeness, to name a few. In this study we analyse these methods providing concrete examples not only to explain how each of them works, but also to facilitate the reader to understand the different usage scenarios in which each of them can be applied. Furthermore, we detail several attacks along with their possible countermeasures, and we discuss open questions and future research directions.

Authors: Antoni Martínez-Ballesté, Hatem Rashwan, Domenec Puig, Agusti Solanas.

Publication date: 2018/6/1

Journal: International Journal of Information Security

Description: Worldwide, thousands of video surveillance cameras record our daily activities. People are aware that video surveillance is deployed for the sake of security. However, the privacy of individuals would be endangered if the proper measures were not considered. Privacy-aware video surveillance has historically been addressed by proposals based on detecting individuals and other sensitive parts of the video and hiding them using a variety of techniques. In this paper, we present a comprehensive solution tackling video processing, video protection and management of the Information System. We claim that a video surveillance system can protect our safety and, at the same time, guarantee our privacy. We describe the design and implementation of a privacy-aware video surveillance platform that, in order to be trustworthy, accomplishes with the properties of high detection accuracy, real-time performance and protected video utility. We have tested the proposed platform, and we demonstrate the feasibility of our approach for privacy protection.

Authors: Fran Casino, Constantinos Patsakis, Agusti Solanas.

Publication date: 2019/11/1

Journal: Electronic Commerce Research and Applications

Description: The amount of available information is growing steadily and, as a result, Internet users benefit from recommender systems, which help them find information, services and products that best fit their needs. A common technique used in recommender systems is Collaborative Filtering, which is based on users’ collaboration to make recommendations. However, users are getting more concerned about their privacy and can be reluctant to disclose their interests and other personal information. Hence, with the aim to foster users collaboration, the development of privacy-aware collaborative filtering methods has become a hot topic in the field. In this article we recall the concept of Privacy-Preserving Collaborative Filtering (PPCF) and introduce a novel approach based on variable-group-size microaggregation, which provides k-anonymity to the users. Also, we introduce several new metrics based on users’ behaviour that overcome the drawbacks of traditional metrics. Extensive experiments show that our approach can provide more accurate recommendations than well-known methods while, at the same time, preserving users’ privacy.

Authors: Agustí Solanas, Josep Domingo-Ferrer, Jordi Castellà-Roca.

Publication date: 2010

Journal: Serbian Publication InfoReview joins UPENET, the Network of CEPIS Societies Journals and Magazines

Description: The use of the new information and communication technologies (ICT) has led to significant changes in the daily development of the information society. Although most of those changes tend to improve our lives, ICT can endanger some of our fundamental rights. In this article, we describe the threats related to the identity of ICT users, and we summarize the countermeasures that can be applied in three especially important areas: Internet search engines, vehicular networks, and location-based services.

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