Delphine Christin

ABSTRACT Mobile phones are increasingly leveraged as sensor platforms to collect information about user's context. The collected sensor readings can however reveal personal and sensitive information about the users and hence put their privacy at stake. In prior work, we have proposed different user interfaces allowing users to select the degree of granularity at which the sensor readings are shared in order to protect their privacy. In this paper, we aim at further increasing user awareness about potential privacy risks and investigate the introduction of picture-based warnings based on their current privacy settings. Depending on their privacy conception and the proposed warnings, users can then adapt their settings or leave them unchanged. We evaluate the picture-based warnings by conducting a user study involving 30 participants. The results show that more than 70% of the participants would change their settings after having seen the picture-based warnings.

ABSTRACT In typical participatory sensing applications, mobile devices record a variety of sensor readings (e.g., sound samples and accelerometer data), which are tagged with spatiotemporal information and uploaded to an application server. The collection of detailed location data reveal insights about the users' whereabouts and daily routines, therefore seriously compromising their privacy. Users can mutually preserve their privacy by opportunistically exchanging sensor readings during physical meetings, thus breaking the link between the collected data and their permanent identities. The success of this procedure depends on the collaboration of all participating users. Our paper proposes a scheme called TrustMeter to assess the individual user contribution to this privacy protection mechanism. Based on peer-based ratings, our system attributes trust levels to each user allowing to readily identify and quarantine malicious users. We investigate the TrustMeters performance under different attacks by means of extensive simulations, and show that it succeeds in quarantining malicious users in most analyzed scenarios.

ABSTRACT Even after more than a decade of research in the field, wireless sensor networks have not yet crossed the chasm: they are still in the early adoption phase and large scale deploy-ments are missing. Sensor network research has long focussed on developing (mostly incremental) improvements on platforms to be, e.g., more simple and/or energy efficient. In this process, the self-imposed limitations led to mainly static deployments of small scale sensor networks. As a result, wireless sensor networks are not yet the commodity envisioned by many researchers in the field of environmental monitoring or pervasive computing. This trend has also impeded research into directions such as mobile sensor networks, which in contrast require platforms with increased complexity. We argue that mobile sensing platforms are well suited for a wide variety of tasks, and they are readily available in the form of mobile phones. We discuss the strengths and limitations of mobile phones against contemporary dedicated sensing platforms and highlight pros and cons in light of realistic application scenarios.