@article {rios2022cpa, title = {Constrained Proximity Attacks on Mobile Targets}, journal = {ACM Transactions on Privacy and Security (TOPS)}, volume = {25}, number = {10}, year = {2022}, month = {05/2022}, pages = {1 - 29}, publisher = {Association for Computer Machinery (ACM)}, abstract = {

Proximity attacks allow an adversary to uncover the location of a victim by repeatedly issuing queries with fake location data. These attacks have been mostly studied in scenarios where victims remain static and there are no constraints that limit the actions of the attacker. In such a setting, it is not difficult for the attacker to locate a particular victim and quantifying the effort for doing so is straightforward. However, it is far more realistic to consider scenarios where potential victims present a particular mobility pattern. In this paper, we consider abstract (constrained and unconstrained) attacks on services that provide location information on other users in the proximity. We derive strategies for constrained and unconstrained attackers, and show that when unconstrained they can practically achieve success with theoretically optimal effort. We then propose a simple yet effective constraint that may be employed by a proximity service (for example, running in the cloud or using a suitable two-party protocol) as countermeasure to increase the effort for the attacker several orders of magnitude both in simulated and real-world cases.

}, keywords = {Location Privacy, mobility pattern, proximity attacks, quantification}, issn = {2471-2566}, doi = {10.1145/3498543}, author = {Xueou Wang and Xiaolu Hou and Ruben Rios and Nils Ole Tippenhauer and Martin Ochoa} } @inproceedings {rios2018mob, title = {Location Proximity Attacks against Mobile Targets: Analytical Bounds and Attacker Strategies}, booktitle = {23rd European Symposium on Research in Computer Security (ESORICS 2018)}, series = {LNCS}, volume = {11099}, year = {2018}, pages = {373-392}, publisher = {Springer}, organization = {Springer}, address = {Barcelona}, abstract = {

Location privacy has mostly focused on scenarios where users remain static. However, investigating scenarios where the victims present a particular mobility pattern is more realistic. In this paper, we consider abstract attacks on services that provide location information on other users in the proximity. In that setting, we quantify the required effort of the attacker to localize a particular mobile victim. We prove upper and lower bounds for the effort of an optimal attacker. We experimentally show that a Linear Jump Strategy\ (LJS) practically achieves the upper bounds for almost uniform initial distributions of victims. To improve performance for less uniform distributions known to the attacker, we propose a Greedy Updating Attack Strategy\ (GUAS). Finally, we derive a realistic mobility model from a real-world dataset and discuss the performance of our strategies in that setting.

}, isbn = {978-3-319-98988-4}, doi = {10.1007/978-3-319-98989-1}, author = {Xueou Wang and Xiaolu Hou and Ruben Rios and Per Hallgren and Nils Ole Tippenhauer and Martin Ochoa} } @article {Lopez2017iotpriv, title = {Evolving privacy: From sensors to the Internet of Things}, journal = {Future Generation Computer Systems}, volume = {75}, year = {2017}, month = {10/2017}, pages = {46{\textendash}57}, publisher = {Elsevier}, abstract = {

The Internet of Things (IoT) envisions a world covered with billions of smart, interacting things capable of offering all sorts of services to near and remote entities. The benefits and comfort that the IoT will bring about are undeniable, however, these may come at the cost of an unprecedented loss of privacy. In this paper we look at the privacy problems of one of the key enablers of the IoT, namely wireless sensor networks, and analyse how these problems may evolve with the development of this complex paradigm. We also identify further challenges which are not directly associated with already existing privacy risks but will certainly have a major impact in our lives if not taken into serious consideration.\ 

}, keywords = {Challenges, Internet of Things, privacy, WSN}, issn = {0167-739X}, doi = {10.1016/j.future.2017.04.045}, author = {Javier Lopez and Ruben Rios and Feng Bao and Guilin Wang} }