TY - GEN
T1 - PAMPAS
T2 - 28th International Conference on Scientific and Statistical Database Management, SSDBM 2016
AU - That, Dai Hai Ton
AU - Popa, Iulian Sandu
AU - Zeitouni, Karine
AU - Borcea, Cristian
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/7/18
Y1 - 2016/7/18
N2 - Mobile participatory sensing could be used in many applications such as vehicular traffic monitoring, pollution tracking, or even health surveying. However, its success depends onfinding a solution for querying large numbers of users which protects user location privacy and works in real-time. This paper presents PAMPAS, a privacy-aware mobile distributed system for efficient data aggregation in mobile participatory sensing. In PAMPAS, mobile devices enhanced with secure hardware, called secure probes (SPs), perform distributed query processing, while preventing users from accessing other users' data. A supporting server infrastructure (SSI) coordinates the inter-SP communication and the computation tasks executed on SPs. PAMPAS ensures that SSI cannot link the location reported by SPs to the user identities even if SSI has additional background information. In addition to its novel system architecture, PAMPAS also proposes two new protocols for privacy-aware location based aggregation and adaptive spatial partitioning of SPs that work efficiently on resourceconstrained SPs. Our experimental results and security analysis demonstrate that these protocols are able to collect the data, aggregate them, and share statistics or derived models in real-time, without any location privacy leakage.
AB - Mobile participatory sensing could be used in many applications such as vehicular traffic monitoring, pollution tracking, or even health surveying. However, its success depends onfinding a solution for querying large numbers of users which protects user location privacy and works in real-time. This paper presents PAMPAS, a privacy-aware mobile distributed system for efficient data aggregation in mobile participatory sensing. In PAMPAS, mobile devices enhanced with secure hardware, called secure probes (SPs), perform distributed query processing, while preventing users from accessing other users' data. A supporting server infrastructure (SSI) coordinates the inter-SP communication and the computation tasks executed on SPs. PAMPAS ensures that SSI cannot link the location reported by SPs to the user identities even if SSI has additional background information. In addition to its novel system architecture, PAMPAS also proposes two new protocols for privacy-aware location based aggregation and adaptive spatial partitioning of SPs that work efficiently on resourceconstrained SPs. Our experimental results and security analysis demonstrate that these protocols are able to collect the data, aggregate them, and share statistics or derived models in real-time, without any location privacy leakage.
KW - Location privacy
KW - distributed architecture
KW - mobile participatory sensing
KW - secure protocol
KW - spatial aggregates
UR - http://www.scopus.com/inward/record.url?scp=84982152452&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84982152452&partnerID=8YFLogxK
U2 - 10.1145/2949689.2949704
DO - 10.1145/2949689.2949704
M3 - Conference contribution
AN - SCOPUS:84982152452
T3 - ACM International Conference Proceeding Series
BT - Scientific and Statistical Database Management
A2 - Baumann, Peter
A2 - Manolescu-Goujot, Ioana
A2 - Trani, Luca
A2 - Ioannidis, Yannis
A2 - Barnafoldi, Gergely Gabor
A2 - Dobos, Laszlo
A2 - Banyai, Evelin
PB - Association for Computing Machinery
Y2 - 18 July 2016 through 20 July 2016
ER -