Abstract
Urban Sensing is an emerging paradigm that combines the ubiquity of smartphones with measurement capabilities of sensor networks. While this concept is still in development, related security and privacy concerns become increasingly more relevant. In this paper, we focus on a number of scenarios where nodes of an Urban Sensing system are subject to individual queries. We address the problem of protecting query privacy (i.e., hiding which node matches the query) and data privacy (i.e., hiding sensed data). We introduce a realistic network model and two novel adversarial models: resident and non-resident adversaries. For each of them, we propose a distributed privacy-preserving technique and evaluate its effectiveness via analysis and simulation. To the best of our knowledge, this is the first attempt to define and address both query and data privacy in the context of Urban Sensing. Our techniques are tunable, trading off the level of privacy assurance with a small overhead increase. We additionally provide a relevant improvement of data reliability and availability, while only relying on standard symmetric cryptography. The practicality of our proposals is demonstrated both analytically and experimentally.
Keywords
- Data Privacy
- Computational Overhead
- Message Overhead
- Private Information Retrieval
- Dissemination Message
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Burke, J., Estrin, D., Hansen, M., Parker, A., Ramanathan, N., Reddy, S., Srivastava, M.: Participatory Sensing. In: World Sensor Web Workshop (2006)
Chang, K., Shin, K.G.: Distributed authentication of program integrity verification in wireless sensor networks. ACM Trans. Inf. Syst. Secur. 11 (2008)
Chaum, D.L.: Untraceable electronic mail, return addresses, and digital pseudonyms. Communications of ACM 24(2) (1981)
Chor, B., Kushilevitz, E., Goldreich, O., Sudan, M.: Private information retrieval. Journal of ACM 45(6) (1998)
Cormen, T., Leiserson, C., Rivest, R., Stein, C.: Introduction to Algorithms. MIT Press, Cambridge (2001)
Cornelius, C., Kapadia, A., Kotz, D., Peebles, D., Shin, M., Triandopoulos, N.: AnonySense: Privacy-aware people-centric sensing. In: MobiSys (2008)
Das, T., Mohan, P., Padmanabhan, V., Ramjee, R., Sharma, A.: PRISM: Platform for Remote Sensing using Smartphones. In: MobiSys (2010)
De Cristofaro, E., Ding, X., Tsudik, G.: Privacy-preserving querying in wireless sensor networks. In: ICCCN (2009)
De Cristofaro, E., Soriente, C.: PEPSI: Privacy-Enhanced Participatory Sensing Infrastructure. In: WiSec (2011)
Ganti, R., Pham, N., Tsai, Y., Abdelzaher, T.: PoolView: Stream Privacy for Grassroots Participatory Sensing. In: SenSys (2008)
Huang, K., Kanhere, S., Hu, W.: Preserving Privacy in Participatory Sensing Systems. Computer Communications 33(11) (2010)
Lee, J., Hoh, B.: Sell Your Experiences: A Market Mechanism based Incentive for Participatory Sensing. In: PerCom (2010)
Lu, H., Pan, W., Lane, N., Choudhury, T., Campbell, A.: SoundSense: Scalable Sound Sensing for People-Centric Applications on Mobile Phones. In: MobiSys (2009)
Machanavajjhala, A., Kifer, D., Gehrke, J., Venkitasubramaniam, M.: l-diversity: Privacy beyond k-anonymity. ACM Trans. on Knowledge Discovery from Data (TKDD) 1(1) (2007)
Mathur, S., Jin, T., Kasturirangan, N., Chandrasekaran, J., Xue, W., Gruteser, M., Trappe, W.: ParkNet: Drive-by Sensing of Road-side Parking Statistics. In: MobiSys (2010)
Menezes, A.: Elliptic curve public key cryptosystems. Kluwer (2002)
Mohan, P., Padmanabhan, V., Ramjee, R.: Rich Monitoring of Road and Traffic Conditions using Mobile Smartphones. In: SenSys (2008)
Ortolani, S., Conti, M., Crispo, B., Di Pietro, R.: Event Handoff Unobservability in WSN. In: Camenisch, J., Kisimov, V., Dubovitskaya, M. (eds.) iNetSec 2010. LNCS, vol. 6555, pp. 20–28. Springer, Heidelberg (2011)
Ortolani, S., Conti, M., Crispo, B., Di Pietro, R.: Events privacy in WSNs: A new model and its application. In: WoWMoM (2011)
Paulos, E., Honicky, R., Goodman, E.: Sensing Atmosphere. In: SenSys Workshops (2007)
Perito, D., Tsudik, G.: Secure Code Update for Embedded Devices Via Proofs of Secure Erasure. In: Gritzalis, D., Preneel, B., Theoharidou, M. (eds.) ESORICS 2010. LNCS, vol. 6345, pp. 643–662. Springer, Heidelberg (2010)
Reddy, S., Estrin, D., Srivastava, M.: Recruitment Framework for Participatory Sensing Data collections. In: Floréen, P., Krüger, A., Spasojevic, M. (eds.) Pervasive Computing. LNCS, vol. 6030, pp. 138–155. Springer, Heidelberg (2010)
Reed, M.G., Syverson, P.F., Goldschlag, D.M.: Anonymous connections and onion routing. IEEE Journal on Selected Areas in Communications 16(4) (1998)
Shi, J., Zhang, R., Liu, Y., Zhang, Y.: PriSense: Privacy-Preserving Data Aggregation in People-Centric Urban Sensing Systems. In: INFOCOM (2010)
Sion, R., Carbunar, B.: On the Computational Practicality of Private Information Retrieval. In: NDSS (2007)
Sweeney, L.: k-Anonymity: A model for Protecting Privacy. Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 10(5) (2002)
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De Cristofaro, E., Di Pietro, R. (2012). Preserving Query Privacy in Urban Sensing Systems. In: Bononi, L., Datta, A.K., Devismes, S., Misra, A. (eds) Distributed Computing and Networking. ICDCN 2012. Lecture Notes in Computer Science, vol 7129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25959-3_17
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DOI: https://doi.org/10.1007/978-3-642-25959-3_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25958-6
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