Abstract
This paper presents a preliminary investigation on the privacy issues involved in the use of location-based services. It is argued that even if the user identity is not explicitly released to the service provider, the geo-localized history of user-requests can act as a quasi-identifier and may be used to access sensitive information about specific individuals. The paper formally defines a framework to evaluate the risk in revealing a user identity via location information and presents preliminary ideas about algorithms to prevent this to happen.
This work is partially supported by NSF under grants IIS-0430402 and IIS-0242237. The work of Bettini is also partially supported by the Italian MIUR (FIRB ”Web-Minds” project N. RBNE01WEJT_005).
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References
Beresford, A., Stajano, F.: Mix Zones: User Privacy in Location-aware Services. In: Proc. IEEE Workshop on Pervasive Computing and Communication Security (PerSec), pp. 127–131. IEEE, Los Alamitos (2004)
Beresford, A., Stajano, F.: Location Privacy in Pervasive Computing. IEEE Pervasive Computing 2(1), 46–55 (2003)
Bettini, C., Jajodia, S., Wang, X.S.: Time Granularities in Databases, Data Mining, and Temporal Reasoning. Springer, Heidelberg (2000)
Bettini, C., Wang, X., Jajodia, S.: Testing complex temporal relationships involving multiple granularities and its application to data mining. In: Proc. of ACM Symposium in Principles of Database Systems (PODS). ACM press, New York (1996)
Chaum, D.: The Dining Cryptographers Problem: Unconditional Sender and Recipient Untraceability. Journal of Cryptology 1(1), 65–75 (1988)
Chaum, D.: Untraceable Electronic Mail, Return Addresses, and Digital Pseudonyms. Communications of the ACM 24(2), 84–88 (1981)
Cuellar, J., Morris, J., Mulligan, D.: Internet Engineering task force geopriv requirements (2002), http://www.ietf.org/html.charters/geopriv-charter.html
Dalenius, T.: Finding a needle in a haystack – or identifying anonymous census record. Journal of Official Statistics 2(3), 329–336 (1986)
Gedik, B., Liu, L.: A Customizable k-Anonymity Model for Protecting Location Privacy. In: The 25th International Conference on Distributed Computing Systems (IEEE ICDCS) (2005)
Goralwalla, I., Leontiev, Y., Özsu, M., Szafron, D., Combi, C.: Temporal Granularity: Completing the Puzzle. J. Intell. Inf. Syst. 16(1), 41–63 (2001)
Gruteser, M., Grunwald, D.: Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking. In: Proc. of MobiSys 2003 (2003)
Gruteser, M., Hoh, B.: On the Anonymity of Periodic Location Samples. In: Hutter, D., Ullmann, M. (eds.) SPC 2005. LNCS, vol. 3450, pp. 179–192. Springer, Heidelberg (2005)
Khatib, L., Morris, R.: Generating Scenarios for Periodic Events with Binary Constraints. In: Proc. of TIME, pp. 67–72. IEEE, Los Alamitos (1999)
Samarati, P.: Protecting Respondents’ Identities in Microdata Release. IEEE Trans. Knowl. Data Eng. 13(6), 1010–1027 (2001)
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Bettini, C., Wang, X.S., Jajodia, S. (2005). Protecting Privacy Against Location-Based Personal Identification. In: Jonker, W., Petković, M. (eds) Secure Data Management. SDM 2005. Lecture Notes in Computer Science, vol 3674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552338_13
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DOI: https://doi.org/10.1007/11552338_13
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