BitTorrent suffers from one fundamental problem: the long-term availability of content. This occurs on a massivescale with 38% of torrents becoming unavailable within the first month. In this paper we explore this problem by performing two large-scale measurement studies including 46K torrents and 29M users. The studies go significantly beyond any previous work by combining per-node, per-torrent and system-wide observations to ascertain the causes, characteristics and repercussions of file unavailability. The study confirms the conclusion from previous works that seeders have a significant impact on both performance and availability. However, we also present some crucial new findings: (i) the presence of seeders is not the sole factor involved in file availability, (ii) 23.5% of nodes that operate in seedless torrents can finish their downloads, and (iii) BitTorrent availability is discontinuous, operating in cycles of temporary unavailability. Due to our new findings, we consider it is important to revisit the solution space; to this end, we perform large-scale trace-based simulations to explore the potential of two abstract approaches.

Confidence in information and communication technology services and systems is crucial for the digital society which we live in, but this confidence is not possible without privacy-enhancing tools and technologies, nor without risks management frameworks that guarantee privacy, data protection, and secure digital identities. This paper provides information on ongoing and recent developments in this area in the European Union (EU) space. We start by providing an overview of EU's General Data Protection Regulation (GDPR) and proceed by identifying challenges concerning GDPR implementation, either technical or organizational. For this, we consider the work currently being done by a set of EU projects on the H2020 DS-08-2017 topic, namely BPR4GDPR, DEFeND, SMOOTH, PDP4E, PAPAYA and PoSeID-on, which address and aim at providing specific, operational solutions for the identified challenges. We briefly present these solutions and discuss the ways in which the projects cooperate and complement each other. Finally, we identify guidelines for further research.

International audienceIn this paper, we present a comprehensive empirical study on the correlations between users' interest similarity and various social features across three interest domains (i.e., movie, music and TV). This study relies on a large dataset, containing 479; 048 users and 5; 263; 351 user-generated interests, captured from Facebook. We identify the social features from three types of the users' information - demographic information (e.g., age, gender, location), social relations (i.e., friendship), and users' interests. The results reveal that the interest similarity follows the homophily principle, which could be further harnessed by various practical applications and service