TY - GEN
T1 - AnonySense
T2 - 6th International Conference on Mobile Systems, Applications, and Services
AU - Cornelius, Cory
AU - Kapadia, Apu
AU - Kotz, David
AU - Peebles, Dan
AU - Shin, Minho
AU - Triandopoulos, Nikos
PY - 2008
Y1 - 2008
N2 - Personal mobile devices are increasingly equipped with the capability to sense the physical world (through cameras, microphones, and accelerometers, for example) and the network world (with Wi-Fi and Bluetooth interfaces). Such devices offer marry new opportunities for cooperative sensing applications. For example, users' mobile phones may contribute data to community-oriented information services, from city-wide pollution monitoring to enterprise-wide detection of unauthorized Wi-Fi access points. This peoplecentric mobile-sensing model introduces a new security challenge in the design of mobile systems: protecting the privacy of participants while allowing their devices to reliably contribute high-quality data to these large-scale applications. We describe Anony Sense, a privacy-aware architecture for realizing pervasive applications based on collaborative, opportunistic sensing by personal mobile devices. AnonySense allows applications to submit sensing tasks that will be distributed across anonymous participating mobile devices, later receiving verified, yet anonymized, sensor data reports back from the field, thus providing the first secure implementation of this participatory sensing model. We describe our trust model, and the security properties that drove the design of the AnonySense system. We evaluate our prototype implementation through experiments that indicate the feasibility of this approach, and through two applications: a Wi-Fi rogue access point detector and a lost-object finder.
AB - Personal mobile devices are increasingly equipped with the capability to sense the physical world (through cameras, microphones, and accelerometers, for example) and the network world (with Wi-Fi and Bluetooth interfaces). Such devices offer marry new opportunities for cooperative sensing applications. For example, users' mobile phones may contribute data to community-oriented information services, from city-wide pollution monitoring to enterprise-wide detection of unauthorized Wi-Fi access points. This peoplecentric mobile-sensing model introduces a new security challenge in the design of mobile systems: protecting the privacy of participants while allowing their devices to reliably contribute high-quality data to these large-scale applications. We describe Anony Sense, a privacy-aware architecture for realizing pervasive applications based on collaborative, opportunistic sensing by personal mobile devices. AnonySense allows applications to submit sensing tasks that will be distributed across anonymous participating mobile devices, later receiving verified, yet anonymized, sensor data reports back from the field, thus providing the first secure implementation of this participatory sensing model. We describe our trust model, and the security properties that drove the design of the AnonySense system. We evaluate our prototype implementation through experiments that indicate the feasibility of this approach, and through two applications: a Wi-Fi rogue access point detector and a lost-object finder.
KW - Anonymity
KW - Mobile sensing
KW - Opportunistic sensing
KW - Privacy
UR - http://www.scopus.com/inward/record.url?scp=57349110591&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=57349110591&partnerID=8YFLogxK
U2 - 10.1145/1378600.1378624
DO - 10.1145/1378600.1378624
M3 - Conference contribution
AN - SCOPUS:57349110591
SN - 9781605581392
T3 - MobiSys'08 - Proceedings of the 6th International Conference on Mobile Systems, Applications, and Services
SP - 211
EP - 224
BT - MobiSys'08 - Proceedings of the 6th International Conference on Mobile Systems, Applications, and Services
Y2 - 17 June 2008 through 20 June 2008
ER -