Personal Privacy Protection within Pervasive RFID Environments

Recent advancements in location tracking technologies have increased the threat to an individual\u27s personal privacy. Radio frequency identification (RFID) technology allows for the identification and potentially continuous tracking of an object or individual, without obtaining the individual\u27s consent or even awareness that the tracking is taking place. Although many positive applications for RFID technology exist, for example in the commercial sector and law enforcement, the potential for abuse in the collection and use of personal information through this technology also exists. Location data linked to other types of personal information allows not only the detection of past spatial travel and activity patterns, but also inferences regarding past and future behavior and preferences. Legislative and technological solutions to deal with the increased privacy threat raised by this and similar tracking technologies have been proposed. Such approaches in isolation have significant limitations. This thesis hypothesizes that an approach may be developed with high potential for sufficiently protecting individual privacy in the use of RFID technologies while also strongly supporting marketplace uses of such tags. The research develops and investigates the limits of approaches that might be us,ed to protect privacy in pervasive RFID surveillance environments. The conclusion is ultimately reached that an approach facilitating individual control over the linking of unique RFID tag ID numbers to personal identity implemented though a combination of legal controls and technological capabilities would be a highly desirable option in balancing the interests of both the commercial sector and the information privacy interests of individuals. The specific model developed is responsive to the core ethical principle of autonomy of the individual and as such is also intended to be more responsive to the needs of individual consumers. The technological approach proposed integrated with enabling privacy legislation and private contract law to enable interactive alteration of privacy preferences should result in marketplace solutions acceptable to both potential commercial users and those being tracked

Personal Privacy Protection within Pervasive RFID Environments

Recent advancements in location tracking technologies have increased the threat to an individual\u27s personal privacy. Radio frequency identification (RFID) technology allows for the identification and potentially continuous tracking of an object or individual, without obtaining the individual\u27s consent or even awareness that the tracking is taking place. Although many positive applications for RFID technology exist, for example in the commercial sector and law enforcement, the potential for abuse in the collection and use of personal information through this technology also exists. Location data linked to other types of personal information allows not only the detection of past spatial travel and activity patterns, but also inferences regarding past and future behavior and preferences. Legislative and technological solutions to deal with the increased privacy threat raised by this and similar tracking technologies have been proposed. Such approaches in isolation have significant limitations. This thesis hypothesizes that an approach may be developed with high potential for sufficiently protecting individual privacy in the use of RFID technologies while also strongly supporting marketplace uses of such tags. The research develops and investigates the limits of approaches that might be us,ed to protect privacy in pervasive RFID surveillance environments. The conclusion is ultimately reached that an approach facilitating individual control over the linking of unique RFID tag ID numbers to personal identity implemented though a combination of legal controls and technological capabilities would be a highly desirable option in balancing the interests of both the commercial sector and the information privacy interests of individuals. The specific model developed is responsive to the core ethical principle of autonomy of the individual and as such is also intended to be more responsive to the needs of individual consumers. The technological approach proposed integrated with enabling privacy legislation and private contract law to enable interactive alteration of privacy preferences should result in marketplace solutions acceptable to both potential commercial users and those being tracked

Context-based Pseudonym Changing Scheme for Vehicular Adhoc Networks

Vehicular adhoc networks allow vehicles to share their information for safety and traffic efficiency. However, sharing information may threaten the driver privacy because it includes spatiotemporal information and is broadcast publicly and periodically. In this paper, we propose a context-adaptive pseudonym changing scheme which lets a vehicle decide autonomously when to change its pseudonym and how long it should remain silent to ensure unlinkability. This scheme adapts dynamically based on the density of the surrounding traffic and the user privacy preferences. We employ a multi-target tracking algorithm to measure privacy in terms of traceability in realistic vehicle traces. We use Monte Carlo analysis to estimate the quality of service (QoS) of a forward collision warning application when vehicles apply this scheme. According to the experimental results, the proposed scheme provides a better compromise between traceability and QoS than a random silent period scheme.Comment: Extended version of a previous paper "K. Emara, W. Woerndl, and J. Schlichter, "Poster: Context-Adaptive User-Centric Privacy Scheme for VANET," in Proceedings of the 11th EAI International Conference on Security and Privacy in Communication Networks, SecureComm'15. Dallas, TX, USA: Springer, June 2015.

Context and Semantic Aware Location Privacy

With ever-increasing computational power, and improved sensing and communication capabilities, smart devices have altered and enhanced the way we process, perceive and interact with information. Personal and contextual data is tracked and stored extensively on these devices and, oftentimes, ubiquitously sent to online service providers. This routine is proving to be quite privacy-invasive, since these service providers mine the data they collect in order to infer more and more personal information about users. Protecting privacy in the rise of mobile applications is a critical challenge. The continuous tracking of users with location- and time-stamps expose their private lives at an alarming level. Location traces can be used to infer intimate aspects of users' lives such as interests, political orientation, religious beliefs, and even more. Traditional approaches to protecting privacy fail to meet users' expectations due to simplistic adversary models and the lack of a multi-dimensional awareness. In this thesis, the development of privacy-protection approaches is pushed further by (i) adapting to concrete adversary capabilities and (ii) investigating the threat of strong adversaries that exploit location semantics. We first study user mobility and spatio-temporal correlations in continuous disclosure scenarios (e.g., sensing applications), where the more frequently a user discloses her location, the more difficult it becomes to protect. To counter this threat, we develop adversary- and mobility-aware privacy protection mechanisms that aim to minimize an adversary's exploitation of user mobility. We demonstrate that a privacy protection mechanism must actively evaluate privacy risks in order to adapt its protection parameters. We further develop an Android library that provides on-device location privacy evaluation and enables any location-based application to support privacy-preserving services. We also implement an adversary-aware protection mechanism in this library with semantic-based privacy settings. Furthermore, we study the effects of an adversary that exploits location semantics in order to strengthen his attacks on user traces. Such extensive information is available to an adversary via maps of points of interest, but also from users themselves. Typically, users of online social networks want to announce their whereabouts to their circles. They do so mostly, if not always, by sharing the type of their location along with the geographical coordinates. We formalize this setting and by using Bayesian inference show that if location semantics of traces is disclosed, users' privacy levels drop considerably. Moreover, we study the time-of-day information and its relation to location semantics. We reveal that an adversary can breach privacy further by exploiting time-dependency of semantics. We implement and evaluate a sensitivity-aware protection mechanism in this setting as well. The battle for privacy requires social awareness and will to win. However, the slow progress on the front of law and regulations pushes the need for technological solutions. This thesis concludes that we have a long way to cover in order to establish privacy-enhancing technologies in our age of information. Our findings opens up new venues for a more expeditious understanding of privacy risks and thus their prevention