Abstract
We present a multidisciplinary solution to an application of private retrieval of location-based information. Our solution is perturbative, is based on the same privacy criterion used in microdata k- anonymization, and provides anonymity through a substantial modification of the Lloyd algorithm, a celebrated quantization design algorithm, endowed with numerical optimization techniques. Specifically, we consider Internet-enabled devices equipped with any sort of location-tracking technology, frequently operative near a fixed reference location, for example a home computer or a cell phone that is most commonly used from the same workplace. Accurate location information is collected by a trusted third party and our modification of the Lloyd algorithm is used to create distortion-optimized, size-constrained clusters, where k nearby devices share a common centroid location. This centroid location is sent back to the devices, which use it when contacting location-based information providers, in lieu of the exact home location, to enforce k- anonymity.
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References
Chaum D (1985) Security without identification: transaction systems to make big brother obsolete. Commun ACM 28(10):1030–1044
Benjumea V, López J, Linero JMT (2006) Specification of a framework for the anonymous use of privileges. Telemat Informat 23(3):179–195
Bianchi G, Bonola M, Falletta V, Proto FS, Teofili S (2008) The SPARTA pseudonym and authorization system. Sci Comput Program 74(1–2):23–33
Gruteser M, Grunwald D (2003) Anonymous usage of location-based services through spatial and temporal cloaking. In: Proceedings of the ACM international conference on mobile systems, applications, and services (MobiSys). ACM, San Francisco, CA, May 2003, pp 31–42
Duckham M, Mason K, Stell J, Worboys M (2001) A formal approach to imperfection in geographic information. Comput Environ Urban Syst 25(1):89–103
Duckham M, Kulit L (2005) A formal model of obfuscation and negotiation for location privacy. In: Proceedings of the international conference on pervasive computing. Lecture Notes in Computer Science (LNCS), vol 3468. Springer, Munich, Germany, May 2005, pp 152–170
Ardagna CA, Cremonini M, Damiani E, De Capitani di Vimercati S, Samarati P (2007) Location privacy protection through obfuscation-based techniques. In: Proceedings of annual IFIP working conference on data and applications security. Lecture Notes in Computer Science (LNCS), vol 4602. Springer, Redondo Beach, CA, Jul 2007, pp 47–60
Chow C, Mokbel MF, Liu X (2006) A peer-to-peer spatial cloaking algorithm for anonymous location-based services. In: Proceedings of the ACM international symposium on advances in geographic information systems (GIS), Arlington, VA, Nov 2006, pp 171–178
Samarati P, Sweeney L (1998) Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression. SRI Int Tech Rep, pp 1–19
Samarati P (2001) Protecting respondents’ identities in microdata release. IEEE Trans Knowl Data Eng 13(6):1010–1027
Truta TM, Vinay B (2006) Privacy protection: p-sensitive k-anonymity property. In: Proceedings of the international workshop on privacy data management (PDM), Atlanta, GA, 2006, p 94
Sun X, Wang H, Li J, Truta TM (2008) Enhanced p-sensitive k-anonymity models for privacy preserving data publishing. Trans Data Privacy 1(2):53–66
Machanavajjhala A, Gehrke J, Kiefer D, Venkitasubramanian M (2006) l-Diversity: privacy beyond k-anonymity. In: Proceedings of the IEEE international conference on data engineering (ICDE), Atlanta, GA, Apr 2006, p 24
Rebollo-Monedero D, Forné J, Domingo-Ferrer J (2008) From t-closeness to PRAM and noise addition via information theory. In: Privacy Stat. Databases (PSD). Lecture Notes in Computer Science (LNCS). Springer, Istambul, Turkey
Domingo-Ferrer J (2006) Microaggregation for database and location privacy. In: Proceedings of the international workshop on next generation information technologies and systems (NGITS). Lecture Notes in Computer Science (LNCS), vol 4032. Springer, Kibbutz Shefayim, Israel, Jul 2006, pp 106–116
Solanas A, Martínez-Ballesté A (2008) A TTP-free protocol for location privacy in location-based services. Comput Commun 31(6):1181–1191
Ghinita G, Kalnis P, Khoshgozaran A, Shahabi C, Tan K-L (2008) Private queries in location based services: anonymizers are not necessary. In: Proceedings of the ACM SIGMOD international conference on management of data, Vancouver, Canada, Jun 2008, pp 121–132
Ostrovsky R, Skeith III WE (2007) A survey of single-database PIR: techniques and applications. In: Proceedings of the international conference on practice and theory in public-Key cryptography (PKC). Lecture Notes in Computer Science (LNCS), vol 4450. Springer, Beijing, China, Sep 2007, pp 393–411
Mokbel MF (2006) Towards privacy-aware location-based database servers. In: Proceedings of the IEEE international conference on data engineering workshops (PDM), Atlanta, GA, p 93
Gedik B, Liu L (2005) A customizable k-anonymity model for protecting location privacy. In: Proceedings of the IEEE international conference on distributed computing systems (ICDS), Columbus, OH, Jun 2005, pp 620–629
Cheng R, Zhang Y, Bertino E, Prabhakar S (2006) Preserving user location privacy in mobile data management infrastructures. In: Proceedings of workshop on privacy enhancing technologies (PET). Lecture Notes in Computer Science (LNCS), vol 4258. Springer, Cambridge, UK, 2006, pp 393–412
Gedik B, Liu L (2008) Protecting location privacy with personalized k-anonymity: architecture and algorithms. IEEE Trans Mob Comput 7(1):1–18
Bamba B, Liu L, Pesti P, Wang T (2008) Supporting anonymous location queries in mobile environments with PrivacyGrid. In: Proceedings of the international world wide web (WWW) conference, Beijing, China, Apr 2008, pp 237–246
Lloyd SP (1982) Least squares quantization in PCM. IEEE Trans Inform Theory IT-28: 129–137
Max J (1960) Quantizing for minimum distortion. IEEE Trans Inform Theory 6(1):7–12
Marquardt D (1963) An algorithm for least-squares estimation of nonlinear parameters. SIAM J Appl Math (SIAP) 11:431–441
Gersho A, Gray RM (1992) Vector quantization and signal compression. Kluwer, Boston, MA
Gray RM, Neuhoff DL (1998) Quantization. IEEE Trans Inform Theory 44:2325–2383
Björck A (1996) Numerical methods for least squares problems. SIAM, Philadelphia, PA
Luenberger DG, Ye Y (2008) Linear and nonlinear programming, 3rd edn. Springer, New York
Acknowledgment
This work was partly supported by the Spanish Research Council (CICYT) through projects CONSOLIDER INGENIO 2010 CSD2007-00004 “ARES,” TSI2007-65393-C02-02 “ITACA,” and TEC-2008-06663-C03-01 “P2PSec.”
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Rebollo-Monedero, D., Forné, J., Soriano, M. (2010). Private Location-Based Information Retrieval via k-Anonymous Clustering. In: Giusto, D., Iera, A., Morabito, G., Atzori, L. (eds) The Internet of Things. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1674-7_41
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DOI: https://doi.org/10.1007/978-1-4419-1674-7_41
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