New Approach for Privacy-Aware Location-Based Service Communications
Location-based services (LBS) are very popular for personal communications in the mobile Internet. In such applications, users make use of the mobile devices to obtain the information of the nearest gas stations, restaurants, banks etc from service provider (SP), as well as identification of the optimal route to reach destination according to user position. Obviously, location data is effective for service provisioning. Therefore, the privacy threat is the inherent problem in LBS. Previous known solutions for privacy-preserving LBS require to blind the location data to SP. Consequently, it certainly suffers from a privacy/quality of service trade-off. We present a new approach to handle such problem for privacy-aware LBS communications. In our protocol, the user submits the exact location to SP to obtain the high quality service, while his location data and the communication transcript cannot be the evidence to be obtained by any third party. Hence the privacy of this user is preserved. We take the deniable (ring) authentication as the building blocks. In this way, it is not necessary for the user to provide coarse location information which would degrade the service quality certainly.
KeywordsPrivacy protection Location based service Deniable authentication
This work is supported by National Natural Science Foundation of China (61402376, U1433130), Chunhui project of the Ministry of Education of China (Z2016150) and the National Key R & D Program of China (2017YFB0802300, 2017YFB0802000).
- 3.Chen, X., & Mu, Y. (2016). Preserving user location privacy for location-based service, GPC 2016. LNCS, 9663, 290–300.Google Scholar
- 4.Cheng, R., Zhang, Y., Bertino, E., & Prabhakar, S. (2006). Preserving user location privacy in mobile data management infrastructures. In Privacy enhancing technology workshop, pp. 393–412.Google Scholar
- 5.Damgard, I. (1992). Towards practical public key systems secure against chosen ciphertext attack. In Crypto 1992, LNCS 576, pp. 445–456.Google Scholar
- 6.Dowsley, R., Hanaoka, G., Imai, H., & Nascimento, Anderson C. A. (2011). Round-optimal deniable ring authentication in the presence of big brother. WISA, LNCS, 6513, 307–321.Google Scholar
- 7.Dwork, C., Naor, M., & Sahai, A. (1998). Concurrent zero-knowledge. In STOC, pp. 409–418.Google Scholar
- 9.Ghinita, G., Kalnis, P., Khoshgozaran, A., Shahabi, C., & Tan, K. L. (2008). Private queries in location based services: Anonymizers are not necessary. In SIGMOD, pp. 121–132.Google Scholar
- 10.Khoshgozaran, A., & Shahabi, C. (2007). Blind evaluation of nearest neighbor queries using space transformation to preserve location privacy. In SSTD 2007, LNCS 4605, pp. 239–257.Google Scholar
- 11.Khoshgozaran, A., Shirani-Mehr, H., & Shahabi, C. (2008). SPIRAL, a scalable private information retrieval approach to location privacy. In MDM 2008.Google Scholar
- 12.Krawczyk, H., & Rabin, T. (2000) Chameleon hashing and signautres. In NDSS, pp. 143–154.Google Scholar
- 14.Lu, H., Jensen, C. S., & Yiu, M. L. (2008). PAD: Privacy-area aware, dummy-based location privacy in mobile services. In MobiDE, pp. 16–23.Google Scholar
- 15.Mascetti, S., Bettini, C., Freni, D., Wang, X. S., & Jajodia, S. (2009). Privacy-aware proximity based services. In MDM, pp. 1140–1143.Google Scholar
- 20.Yiu, M. L., Jensen, C. S., Huang, X., & Lu, H. (2008). Spacetwist: managing the trade-offs among location privacy, query performance, and query accuracy in mobile services. ICDE, 2008, 366–375.Google Scholar