Privacy-preserving Publication of Mobility Data with High Utility

An increasing amount of mobility data is being collected every day by different means, e.g., by mobile phone operators. This data is sometimes published after the application of simple anonymization techniques, which might lead to severe privacy threats. We propose in this paper a new solution whose novelty is twofold. Firstly, we introduce an algorithm designed to hide places where a user stops during her journey (namely points of interest), by enforcing a constant speed along her trajectory. Secondly, we leverage places where users meet to take a chance to swap their trajectories and therefore confuse an attacker.Comment: 2015 35th IEEE International Conference on Distributed Computed System

Time Distortion Anonymization for the Publication of Mobility Data with High Utility

An increasing amount of mobility data is being collected every day by different means, such as mobile applications or crowd-sensing campaigns. This data is sometimes published after the application of simple anonymization techniques (e.g., putting an identifier instead of the users' names), which might lead to severe threats to the privacy of the participating users. Literature contains more sophisticated anonymization techniques, often based on adding noise to the spatial data. However, these techniques either compromise the privacy if the added noise is too little or the utility of the data if the added noise is too strong. We investigate in this paper an alternative solution, which builds on time distortion instead of spatial distortion. Specifically, our contribution lies in (1) the introduction of the concept of time distortion to anonymize mobility datasets (2) Promesse, a protection mechanism implementing this concept (3) a practical study of Promesse compared to two representative spatial distortion mechanisms, namely Wait For Me, which enforces k-anonymity, and Geo-Indistinguishability, which enforces differential privacy. We evaluate our mechanism practically using three real-life datasets. Our results show that time distortion reduces the number of points of interest that can be retrieved by an adversary to under 3 %, while the introduced spatial error is almost null and the distortion introduced on the results of range queries is kept under 13 % on average.Comment: in 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, Aug 2015, Helsinki, Finlan

Differentially Private Location Privacy in Practice

With the wide adoption of handheld devices (e.g. smartphones, tablets) a large number of location-based services (also called LBSs) have flourished providing mobile users with real-time and contextual information on the move. Accounting for the amount of location information they are given by users, these services are able to track users wherever they go and to learn sensitive information about them (e.g. their points of interest including home, work, religious or political places regularly visited). A number of solutions have been proposed in the past few years to protect users location information while still allowing them to enjoy geo-located services. Among the most robust solutions are those that apply the popular notion of differential privacy to location privacy (e.g. Geo-Indistinguishability), promising strong theoretical privacy guarantees with a bounded accuracy loss. While these theoretical guarantees are attracting, it might be difficult for end users or practitioners to assess their effectiveness in the wild. In this paper, we carry on a practical study using real mobility traces coming from two different datasets, to assess the ability of Geo-Indistinguishability to protect users' points of interest (POIs). We show that a curious LBS collecting obfuscated location information sent by mobile users is still able to infer most of the users POIs with a reasonable both geographic and semantic precision. This precision depends on the degree of obfuscation applied by Geo-Indistinguishability. Nevertheless, the latter also has an impact on the overhead incurred on mobile devices resulting in a privacy versus overhead trade-off. Finally, we show in our study that POIs constitute a quasi-identifier for mobile users and that obfuscating them using Geo-Indistinguishability is not sufficient as an attacker is able to re-identify at least 63% of them despite a high degree of obfuscation.Comment: In Proceedings of the Third Workshop on Mobile Security Technologies (MoST) 2014 (http://arxiv.org/abs/1410.6674

COCOA: COnversation-based service COmposition in pervAsive computing environments with QoS support

International audienceNo abstrac

AcTinG: Accurate Freerider Tracking in Gossip

Abstract-Gossip-based content dissemination protocols are a scalable and cheap alternative to centralised content sharing systems. However, it is well known that these protocols suffer from rational nodes, i.e., nodes that aim at downloading the content without contributing their fair share to the system. While the problem of rational nodes that act individually has been well addressed in the literature, colluding rational nodes is still an open issue. Indeed, LiFTinG, the only existing gossip protocol addressing this issue, yields a high ratio of false positive accusations of correct nodes. In this paper, we propose AcTinG, a protocol that prevents rational collusions in gossip-based content dissemination protocols, while guaranteeing zero false positive accusations. We assess the performance of AcTinG on a testbed comprising 400 nodes running on 100 physical machines, and compare its behaviour in the presence of colluders against two state-of-the-art protocols: BAR Gossip that is the most robust protocol handling non-colluding rational nodes, and LiFTinG, the only existing gossip protocol that handles colluding nodes. The performance evaluation shows that AcTinG is able to deliver all messages despite the presence of colluders, whereas both LiFTinG and BAR Gossip suffer heavy message loss. It also shows that AcTinG is resilient to massive churn. Finally, using simulations involving up to a million nodes, we show that AcTinG exhibits similar scalability properties as standard gossip-based dissemination protocols

CYCLOSA: Decentralizing Private Web Search Through SGX-Based Browser Extensions

By regularly querying Web search engines, users (unconsciously) disclose large amounts of their personal data as part of their search queries, among which some might reveal sensitive information (e.g. health issues, sexual, political or religious preferences). Several solutions exist to allow users querying search engines while improving privacy protection. However, these solutions suffer from a number of limitations: some are subject to user re-identification attacks, while others lack scalability or are unable to provide accurate results. This paper presents CYCLOSA, a secure, scalable and accurate private Web search solution. CYCLOSA improves security by relying on trusted execution environments (TEEs) as provided by Intel SGX. Further, CYCLOSA proposes a novel adaptive privacy protection solution that reduces the risk of user re- identification. CYCLOSA sends fake queries to the search engine and dynamically adapts their count according to the sensitivity of the user query. In addition, CYCLOSA meets scalability as it is fully decentralized, spreading the load for distributing fake queries among other nodes. Finally, CYCLOSA achieves accuracy of Web search as it handles the real query and the fake queries separately, in contrast to other existing solutions that mix fake and real query results

Semantics-Aware Services for the Mobile Computing Environment

Today's wireless networks and devices support the dynamic composition of mobile distributed systems according to networked services and resources. This has in particular led to the introduction of a number of computing paradigms, among which the Service-Oriented Architecture (SOA) seems to best serve these objectives. However, common SOA solutions restrict considerably the openness of dynamic mobile systems in that they assume a specific middleware infrastructure, over which composed system components have been pre-developed to integrate. On the other hand, the Semantic Web introduces a promising approach towards the integration of heterogeneous components; current semantics-based approaches are, however, restricted to application-level interoperability. Combining the elegant properties of software architecture modeling with the semantic reasoning power of the Semantic Web paradigm, this paper introduces abstract semantic modeling of mobile services that allows both machine reasoning about service composability and enhanced interoperability at both middleware and application level

Towards ad hoc contextual services for pervasive computing

International audienceContext-awareness is a key challenge for pervasive computing, as it is a prime requirement towards delivering applications to users in a way that best matches user requirements, digital resources availability and physical conditions. However, enabling anytime, anywhere context-awareness, as targeted by pervasive computing, is further challenged by the openness of the environment, which requires making available context information in various computing environments. This then calls for the ad hoc networking of context sources and of context-aware applications, so that applications may always benefit from a context knowledge base, although it may be more or less rich, depending on the specific environment. Building upon the context management literature, and the Service-Oriented Architecture (SOA) paradigm that is a major enabler of open ad hoc networking, this paper sketches key context-aware system concepts that need be incorporated in the SOA style towards enabling context-aware services for pervasive computing