Siam U. Hussain
ABSTRACT
This paper presents the first provably secure localization method for smart automotive systems. Using this method, a lost car can compute its location with assistance from three nearby cars while the locations of all the participating cars including the lost car remain private. This localization application is one of the very first location-based services that does not sacrifice accuracy to maintain privacy. The secure location is computed using a protocol utilizing Yao's Garbled Circuit (GC) that allows two parties to jointly compute a function on their private inputs. We design and optimize GC netlists of the functions required for computation of location by leveraging conventional logic synthesis tools. Proof-of-concept implementation of the protocol shows that the complete operation can be performed within only 550 ms. The fast computing time enables practical localization of moving cars.
- J. Hubaux, S. Capkun, and J. Luo, "The security and privacy of smart vehicles," in IEEE S & P, 2004. Google Scholar
Digital Library
- "Automotive security best practices - intel," 2015.Google Scholar
- P. Papadimitratos, L. Buttyan, T. Holczer, E. Schoch, J. Freudiger, M. Raya, Z. Ma, F. Kargl, A. Kung, and J. Hubaux, "Secure vehicular communication systems: design and architecture," in IEEE CM, 2008. Google ScholarDigital Library
- R. Cheng, Y. Zhang, E. Bertino, and S. Prabhakar, "Preserving user location privacy in mobile data management infrastructures," in Privacy Enhancing Technologies, Springer, 2006. Google ScholarDigital Library
- P. Kalnis, G. Ghinita, K. Mouratidis, and D. Papadias, "Preventing location-based identity inference in anonymous spatial queries," in IEEE ITKDE, 2007. Google ScholarDigital Library
- M. Gruteser and D. Grunwald, "Anonymous usage of location-based services through spatial and temporal cloaking," in ICMSAS, ACM, 2003. Google ScholarDigital Library
- A. Khoshgozaran and C. Shahabi, "Blind evaluation of nearest neighbor queries using space transformation to preserve location privacy," in ASTD, Springer, 2007. Google ScholarDigital Library
- G. Zhong, I. Goldberg, and U. Hengartner, "Louis, lester and pierre: Three protocols for location privacy," in Privacy Enhancing Technologies, Springer, 2007. Google ScholarDigital Library
- G. Ghinita, P. Kalnis, A. Khoshgozaran, C. Shahabi, and K. Tan, "Private queries in location based services: anonymizers are not necessary," in SIGMOD ICMD, ACM, 2008. Google ScholarDigital Library
- A. Yao, "How to generate and exchange secrets," in IEEE FOCS, 1986. Google ScholarDigital Library
- Y. Huang, D. Evans, and J. Katz, "Private set intersection: Are garbled circuits better than custom protocols?," in NDSS, 2012.Google Scholar
- Brenner, Perl, and Smith, "hcrypt SFE project." https://hcrypt.com/sfe/.Google Scholar
- E. M. Songhori, S. U. Hussain, A. Sadeghi, T. Schneider, and F. Koushanfar, "Tinygarble: Highly compressed and scalable sequential garbled circuits," in IEEE S&P, 2015. Google ScholarDigital Library
- C. Clifton, M. Kantarcioglu, J. Vaidya, X. Lin, and M. Zhu, "Tools for privacy preserving distributed data mining," in SIGKDD Explorations Newsletter, 2002. Google ScholarDigital Library
- B. Kreuter, A. Shelat, B. Mood, and K. R. Butler, "PCF: A portable circuit format for scalable two-party secure computation.," in USENIX Security, 2013. Google ScholarDigital Library
- M. Bellare, V. T. Hoang, S. K., and P. Rogaway, "Efficient garbling from a fixed-key blockcipher," in IEEE S&P, 2013. Google ScholarDigital Library
- Y. Lindell and B. Pinkas, "Secure two-party computation via cut-and-choose oblivious transfer," in Journal of Cryptology, Springer, 2012. Google ScholarDigital Library
- M. Naor and B. Pinkas, "Computationally secure oblivious transfer," in Journal of Cryptology, Springer, 2005. Google ScholarDigital Library
- V. Kolesnikov and T. Schneider, "Improved garbled circuit: Free xor gates and applications," in ICALP, Springer, 2008. Google ScholarDigital Library
- M. Naor, B. Pinkas, and R. Sumner, "Privacy preserving auctions and mechanism design," in CEC, ACM, 1999. Google ScholarDigital Library
- S. Zahur, M. Rosulek, and D. Evans, "Two halves make a whole: Reducing data transfer in garbled circuits using half gates." Cryptology ePrint Archive, 2014. http://eprint.iacr.org/2014/756.Google Scholar
- Y. Shang, Z. Liu, J. Wang, and X. Xiao, "Triangle and centroid localization algorithm based on distance compensation," in ICISCE, IET, 2012.Google Scholar
- A. Bensky, Wireless positioning technologies and applications. Artech House, 2007. Google ScholarDigital Library
- "Intel Atom Processor E3845." ark.intel.com/products/78475, 2015.Google Scholar
- "IEEE 1609 - family of standards for wireless access in vehicular environments (WAVE)." standards.its.dot.gov/factsheets/factsheet/80, 2009.Google Scholar
- M. Atallah and W. Du, "Secure multi-party computational geometry," in Algorithms and Data Structures, Springer, 2001. Google ScholarDigital Library
- Y. Huang and R. Vishwanathan, "Privacy preserving group nearest neighbour queries in location-based services using cryptographic techniques," in IEEE GLOBECOM, 2010.Google Scholar
- E. Songhori, S. Hussain, A. Sadeghi, and F. Koushanfar, "Compacting privacy-preserving k-nearest neighbor search using logic synthesis," in DAC, 2015. Google ScholarDigital Library
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