AnonySense: Opportunistic and Privacy-Preserving Context Collection

Opportunistic sensing allows applications to "task" mobile devices to measure context in a target region. For example, one could leverage sensorequipped vehicles to measure traffic or pollution levels on a particular street, or users' mobile phones to locate (Bluetooth-enabled) objects in their neighborhood. In most proposed applications, context reports include the time and location of the event, putting the privacy of users at increased risk--even if a report has been anonymized, the accompanying time and location can reveal sufficient information to deanonymize the user whose device sent the report. We propose AnonySense, a general-purpose architecture for leveraging users' mobile devices for measuring context, while maintaining the privacy of the users. AnonySense features multiple layers of privacy protection--a framework for nodes to receive tasks anonymously, a novel blurring mechanism based on tessellation and clustering to protect users' privacy agains...

• Type: Journal
• Year: 2008
• Where: PERVASIVE
• Authors: Apu Kapadia, Nikos Triandopoulos, Cory Cornelius, Daniel Peebles, David Kotz
• Keywords: Applied Computing, Mobile Devices, PERVASIVE 2008, Privacy, Report