Mathieu Cunche

Abhishek Kumar Mishra, Mathieu Cunche, Heber H. Arcolezi

Mobility traces are among the most revealing forms of personal data, yet trajectory releases are often protected only by ad hoc transformations. We stress-test such practices on recently-released YJMob100K, an anonymized dataset of 100,000 user trajectories in Japan. First, we show that the applied protection leaves enough spatial and temporal structure to recover both the real-world geographic frame and the actual calendar timeline by exploiting density signatures, urban correlations, and temporal activity profiles. On top of this reconstruction, we quantify privacy risks through trajectory-level metrics that capture spatio-temporal k-anonymity, -point unicity, home-work and multi-anchor uniqueness, and exposure to secluded and sensitive locations. These metrics reveal extensive re-identification surfaces: a small number of observations, anchors, or sensitive venues often suffices to uniquely pinpoint users or their social neighborhoods. Finally, we evaluate representative sanitization strategies: geo-indistinguishability, local differential privacy, and aggressive spatial de-structuring; and observe a consistent pattern: strong privacy parameters destroy downstream utility, while utility-preserving settings leave structural leakage largely intact. Overall, our findings show that current sanitization techniques are insufficient for large-scale mobility data, and they highlight the urgent need for trajectory-aware privacy mechanisms and stronger publication standards.

Claude Castelluccia, Nataliia Bielova, Antoine Boutet et al.

This document presents an evolution of the ROBERT protocol that decentralizes most of its operations on the mobile devices. DESIRE is based on the same architecture than ROBERT but implements major privacy improvements. In particular, it introduces the concept of Private Encounter Tokens, that are secret and cryptographically generated, to encode encounters. In the DESIRE protocol, the temporary Identifiers that are broadcast on the Bluetooth interfaces are generated by the mobile devices providing more control to the users about which ones to disclose. The role of the server is merely to match PETs generated by diagnosed users with the PETs provided by requesting users. It stores minimal pseudonymous data. Finally, all data that are stored on the server are encrypted using keys that are stored on the mobile devices, protecting against data breach on the server. All these modifications improve the privacy of the scheme against malicious users and authority. However, as in the first version of ROBERT, risk scores and notifications are still managed and controlled by the server of the health authority, which provides high robustness, flexibility, and efficacy.

Marco Fiore, Panagiota Katsikouli, Elli Zavou et al.

We survey the literature on the privacy of trajectory micro-data, i.e., spatiotemporal information about the mobility of individuals, whose collection is becoming increasingly simple and frequent thanks to emerging information and communication technologies. The focus of our review is on privacy-preserving data publishing (PPDP), i.e., the publication of databases of trajectory micro-data that preserve the privacy of the monitored individuals. We classify and present the literature of attacks against trajectory micro-data, as well as solutions proposed to date for protecting databases from such attacks. This paper serves as an introductory reading on a critical subject in an era of growing awareness about privacy risks connected to digital services, and provides insights into open problems and future directions for research.

Abdelberi Chaabane, Terence Chen, Mathieu Cunche et al.

Internet censorship is enforced by numerous governments worldwide, however, due to the lack of publicly available information, as well as the inherent risks of performing active measurements, it is often hard for the research community to investigate censorship practices in the wild. Thus, the leak of 600GB worth of logs from 7 Blue Coat SG-9000 proxies, deployed in Syria to filter Internet traffic at a country scale, represents a unique opportunity to provide a detailed snapshot of a real-world censorship ecosystem. This paper presents the methodology and the results of a measurement analysis of the leaked Blue Coat logs, revealing a relatively stealthy, yet quite targeted, censorship. We find that traffic is filtered in several ways: using IP addresses and domain names to block subnets or websites, and keywords or categories to target specific content. We show that keyword-based censorship produces some collateral damage as many requests are blocked even if they do not relate to sensitive content. We also discover that Instant Messaging is heavily censored, while filtering of social media is limited to specific pages. Finally, we show that Syrian users try to evade censorship by using web/socks proxies, Tor, VPNs, and BitTorrent. To the best of our knowledge, our work provides the first analytical look into Internet filtering in Syria.