Abstract
SMC is a problem of n parties with inputs (x1, x2…xn) , hand over their inputs to third party for computation f(x1, x2…xn) and third party announces the result in the form of y. During joint computation of inputs, all the organizations involved in computation wish to preserve privacy of their inputs. So need is to define a protocol which maintains privacy, security and correctness parameters of SMC. In this paper, single third party and multi third party model are defined and compared. The probabilistic evidences for single and multi third party SMC model have been analyzed with security analysis graphs. In this paper, we have also worked on identification and reduction of malicious conduct of TTPs in multi TTP environment.
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References
Clifton, C., Kantarcioglu, M., Vaidya, J., Lin, X., Michael, Y.: Tools for privacy preserving distributed data mining. SIGKDD Explorations 4(2), 1–8 (2002)
Vaidya, J., Clifton, C.: Leveraging the Multi in Secure Multi-Party Computation. In: Proceeding of the 2003 ACM Workshop on Privacy in Electronic Society. ACM Press (2003)
Yao, A.C.: Protocol for secure computations. In: Proc. 23rd IEEE Symposium on the Foundation of Computer Science (FOCS), pp. 160–164. IEEE (1982)
Goldreich, O., Micali, S., Wigderson, A.: How to play any mental game- a complete theorem for protocol with honest majority. In: Proceeding of 19th ACM Symposium on the Theory of Computing (STOC), pp. 218–229 (1987)
Ioannidis, I., Grama, A.: An efficient protocol for Yao’s Millionaires Problem. In: Proceeding of 36th Hawaii International Conference on System Sciences, HICSS 2003, pp. 6–11. IEEE Press (2003)
Goldreich, O., Micali, S., Wigderson, A.: How to play any mental game. In: Proceedings of the Nineteenth Annual ACM Conference on Theory of Computing, STOC 1987, pp. 218–229. ACM, New York (1987)
Chor, B., Gilbao, N.: Computationally Private Information Retrieval (Extended Abstract). In: Proceedings of 29th Annual ACM Symposium on Theory of Computing, El Paso, TX, USA (1997)
Chor, B., Kushilevitz, E., Goldreich, O., Sudan, M.: Private Information Retrieval. In: Proceedings of the 36th Annual IEEE Symposium on Foundations of Computer Science, Milwaukee, WI, pp. 41–50 (1995)
Lindell, Y., Pinkas, B.: Privacy Preserving Data Mining. In: Bellare, M. (ed.) CRYPTO 2000. LNCS, vol. 1880, pp. 36–54. Springer, Heidelberg (2000)
Agrawal, R., Srikant, R.: Privacy-Preserving Data Mining. In: Proceedings of the 2000 ACM SIGMOD on Management of Data, Dallas, TX, USA, pp. 439–450 (2000)
Atallah, M.J., Du, W.: Secure Multiparty Computational Geometry. In: Proceedings of Seventh International Workshop on Algorithms and Data Structures (WADS 2001), Providence, Rhode Island, USA, pp. 165–179 (2001)
Du, W., Atallah, M.J.: Privacy-Preserving Cooperative Scientific Computations. In: 14th IEEE Computer Security Foundations Workshop, Nova Scotia, Canada, June 11-13, pp. 273–282 (2001)
Du, W., Atallah, M.J.: Privacy-Preserving Statistical Analysis. In: Proceedings of the 17th Annual Computer Security Applications Conference, New Orleans, Louisiana, USA, pp. 102–110 (2001)
Du, W., Atallah, M.J.: Secure Multiparty Computation Problems and Their Applications: A Review and Open Problems. In: Proceedings of New Security Paradigm Workshop, Cloudcroft, New Maxico, USA, pp. 11–20 (2001)
Oleshchuk, V., Zadorozhny, V.: Secure Multi-Party Computations and Privacy Preservation: Results and Open Problems. Telektronikk: Telenor’s Journal of Technology 103(2) (2007)
Zheng, Q., Shan Luo, S., Xin, Y.: Research on the Secure Multi-Party Computation of some Linear Algebra Problems. Applied Mechanics and Materials. Trans. Tech. Publication 20-23, 265–270 (2010)
Henecka, W., Ogl, S.K.: TASTY: tool for automating secure two-party computations. In: The Proceedings of the 17th ACM Conference on Computer and Communications Security (2010)
Lucas, C., Raub, D., Maurer, U.: Hybrid-secure MPC: trading information-theoretic robustness for computational privacy. In: Proceeding of the 29th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing, PODC 2010 (2010)
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Shaikh, Z., Garg, P. (2012). Single and Multi Trusted Third Party: Comparison, Identification and Reduction of Malicious Conduct by Trusted Third Party in Secure Multiparty Computing Protocol. In: Wyld, D., Zizka, J., Nagamalai, D. (eds) Advances in Computer Science, Engineering & Applications. Advances in Intelligent Systems and Computing, vol 167. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30111-7_28
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DOI: https://doi.org/10.1007/978-3-642-30111-7_28
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