Dynamic privacy management in pervasive sensor networks

This paper describes the design and implementation of a dynamic privacy management system aimed at enabling tangible privacy control and feedback in a pervasive sensor network. Our work began with the development of a potentially invasive sensor network (with high resolution video, audio, and motion tracking capabilities) featuring different interactive applications that created incentive for accepting this network as an extension of people’s daily social space. A user study was then conducted to evaluate several privacy management approaches – an active badge system for both online and on-site control, on/off power switches for physically disabling the hardware, and touch screen input control. Results from a user study indicated that an active badge for on-site privacy control is the most preferable method among all provided options. We present a set of results that yield insight into the privacy/benefit tradeoff from various sensing capabilities in pervasive sensor networks and how privacy settings and user behavior relate in these environments.Things That Think Consortiu

Big Brother Knows Your Friends: on Privacy of Social Communities in Pervasive Networks

Wireless network operators increasingly deploy WiFi hotspots and low-power, low-range base stations in order to satisfy users' growing demands for context-aware services and performance. In addition to providing better service, such capillary infrastructure deployment threatens users' privacy with respect to their social ties and communities, as it allows infrastructure owners to infer users' daily social encounters with increasing accuracy, much to the detriment of their privacy. Yet, to date, there are no evaluations of the privacy of communities in pervasive wireless networks. In this paper, we address the important issue of privacy in pervasive communities by experimentally evaluating the accuracy of an adversary-owned set of wireless sniffing stations in reconstructing the communities of mobile users. During a four-month trial, 80 participants carried mobile devices and were eavesdropped on by an adversarial wireless mesh network on a university campus. To the best of our knowledge, this is the first study that focuses on the privacy of communities in a deployed pervasive network and provides important empirical evidence on the accuracy and feasibility of community tracking in such networks

A Clustering-based Location Privacy Protection Scheme for Pervasive Computing

In pervasive computing environments, Location- Based Services (LBSs) are becoming increasingly important due to continuous advances in mobile networks and positioning technologies. Nevertheless, the wide deployment of LBSs can jeopardize the location privacy of mobile users. Consequently, providing safeguards for location privacy of mobile users against being attacked is an important research issue. In this paper a new scheme for safeguarding location privacy is proposed. Our approach supports location K-anonymity for a wide range of mobile users with their own desired anonymity levels by clustering. The whole area of all users is divided into clusters recursively in order to get the Minimum Bounding Rectangle (MBR). The exact location information of a user is replaced by his MBR. Privacy analysis shows that our approach can achieve high resilience to location privacy threats and provide more privacy than users expect. Complexity analysis shows clusters can be adjusted in real time as mobile users join or leave. Moreover, the clustering algorithms possess strong robustness.Comment: The 3rd IEEE/ACM Int Conf on Cyber, Physical and Social Computing (CPSCom), IEEE, Hangzhou, China, December 18-20, 201

On Facebook, most ties are weak

Pervasive socio-technical networks bring new conceptual and technological challenges to developers and users alike. A central research theme is evaluation of the intensity of relations linking users and how they facilitate communication and the spread of information. These aspects of human relationships have been studied extensively in the social sciences under the framework of the "strength of weak ties" theory proposed by Mark Granovetter.13 Some research has considered whether that theory can be extended to online social networks like Facebook, suggesting interaction data can be used to predict the strength of ties. The approaches being used require handling user-generated data that is often not publicly available due to privacy concerns. Here, we propose an alternative definition of weak and strong ties that requires knowledge of only the topology of the social network (such as who is a friend of whom on Facebook), relying on the fact that online social networks, or OSNs, tend to fragment into communities. We thus suggest classifying as weak ties those edges linking individuals belonging to different communities and strong ties as those connecting users in the same community. We tested this definition on a large network representing part of the Facebook social graph and studied how weak and strong ties affect the information-diffusion process. Our findings suggest individuals in OSNs self-organize to create well-connected communities, while weak ties yield cohesion and optimize the coverage of information spread.Comment: Accepted version of the manuscript before ACM editorial work. Check http://cacm.acm.org/magazines/2014/11/179820-on-facebook-most-ties-are-weak/ for the final versio

Configurable dynamic privacy for pervasive sensor networks

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 76-79).Ubiquitous computing sensor networks have greatly augmented the functionality of interactive media systems by adding the ability to capture and store activity-related information. Analyzing the information recorded from pervasive sensor networks can provide insight about human behavior for better personalized system services, as well as richer media content and social communication. With these increased capabilities, serious concerns which create great obstacles to the deployment of such network are raised with regard to privacy and boundaries. However, there exist no real data currently about privacy in pervasive media networks and most studies that have been made so far are speculative. This thesis presents the design and implementation of a configurable infrastructure that can protect users' dynamic levels of privacy in a pervasive sensor network. Through an active badge system, users have different options to disable each type of data transmission. This work evaluates approaches for privacy protection through conducting an extensive user study in an actual ubiquitous invasive sensing environment to obtain feedback via sensor system data and questionnaires and correlates that information for future reference in the design of privacy-protected ubiquitous sensor networks. Results from the user study indicated that an active badge for on-site control, especially periodically broadcast RF beacon for privacy control, is the most effective and acceptable method.(cont.) However, it also suggested that if every occupant in the building used this approach to constantly block all data transmission, significant system blinding (on the order of 30 % or more) would be incurred. These results allow a better understanding of what value is assessed to privacy versus capabilities/awareness beyond the current assumptions.by Nan-Wei Gong.S.M

Emotions in context: examining pervasive affective sensing systems, applications, and analyses

Pervasive sensing has opened up new opportunities for measuring our feelings and understanding our behavior by monitoring our affective states while mobile. This review paper surveys pervasive affect sensing by examining and considering three major elements of affective pervasive systems, namely; “sensing”, “analysis”, and “application”. Sensing investigates the different sensing modalities that are used in existing real-time affective applications, Analysis explores different approaches to emotion recognition and visualization based on different types of collected data, and Application investigates different leading areas of affective applications. For each of the three aspects, the paper includes an extensive survey of the literature and finally outlines some of challenges and future research opportunities of affective sensing in the context of pervasive computing

In Things We Trust? Towards trustability in the Internet of Things

This essay discusses the main privacy, security and trustability issues with the Internet of Things

Interpretable Machine Learning for Privacy-Preserving Pervasive Systems

Our everyday interactions with pervasive systems generate traces that capture various aspects of human behavior and enable machine learning algorithms to extract latent information about users. In this paper, we propose a machine learning interpretability framework that enables users to understand how these generated traces violate their privacy