Abstract
Secure sum allows cooperating parties to compute sum of their private data without revealing their individual data to one another. Many secure sum protocols exists in the literature. Most of them assume network to be secure. In this paper we drop that assumption and provide a protocol that is applicable to insecure networks as well. We used additive homomorphic encryption technique for secure sum computation.
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References
Clifton C, Kantarcioglu M, Vaidya J, Lin X, Zhu MY (2002) Tools for privacy-preserving distributed data mining. J. SIGKDD Explor Newsl 4(2):28–34. ACM Press
Sheikh R, Kumar B, Mishra DK (2010) Changing neighbors k-secure sum protocol for secure multi-party computation. Int J of Comput Sci Inf Secur, USA, 7(1) (Accepted for publication)
Sheikh R, Kumar B, Mishra DK (2009) Privacy-preserving k-secure sum protocol. Int J Comput Sci Inf Secur, USA, 6(2):184–188
Sheikh R, Kumar B, Mishra DK (2009) A distributed k-secure sum protocol for secure multi-party computation. Submitted to a journal
Yao AC (1982) Protocol for secure computations. In: Proceedings of the 23rd annual IEEE symposium on foundation of computer science, pp 160–164
Goldreich O, Micali S, Wigderson A (1987) How to play any mental game. In: STOC’87: Proceedings of the nineteenth annual ACM conference on theory of computing, New York, NY, USA: ACM, pp 218–229
Chor B, Gilbao N (1997) Computationally private information retrieval (extended abstract). In: Proceedings of 29th annual ACM symposium on theory of computing, El Paso, TX USA, May 1997
Chor B, Kushilevitz E, Goldreich O, Sudan M (1995) Private information retrieval. In: Proceedings of the 36th annual IEEE symposium on foundations of computer science, Milwaukee WI, pp 41–50, Oct 1995
Lindell Y, Pinkas B (2000) Privacy preserving data mining in advances in cryptography-Crypto2000, lecture notes in computer science, vol 1880
Agrawal R, Srikant R (2000) Privacy-preserving data mining. In: Proceedings of the 2000 ACM SIGMOD on management of data, Dallas, TX USA, pp 439–450, 15–18 May 2000
Atallah MJ, Du W (2001) Secure multiparty computational geometry. In: Proceedings of seventh international workshop on algorithms and data structures (WADS2001). Providence, Rhode Island, USA, pp 165–179, 8–10 Aug 2001
Du W, Atallah MJ (2001) Privacy-preserving cooperative scientific computations. In: 14th IEEE computer security foundations workshop, Nova Scotia, Canada, pp 273–282, 11–13 Jun 2001
Du W, Atallah MJ (2001) Privacy-preserving statistical analysis. In: Proceedings of the 17th annual computer security applications conference, New Orleans, Louisiana, USA, pp 102–110, 10–14 Dec 2001
Paillier P (1999) Public-key cryptosystems based on composite degree residuosity classes. In: EUROCRYPT’99, Prague, Czech Republic, pp 223–238, 2–6 May 1999
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Sheikh, R., Mishra, D.K. (2019). Secure Sum Computation Using Homomorphic Encryption. In: Mishra, D., Yang, XS., Unal, A. (eds) Data Science and Big Data Analytics. Lecture Notes on Data Engineering and Communications Technologies, vol 16. Springer, Singapore. https://doi.org/10.1007/978-981-10-7641-1_31
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DOI: https://doi.org/10.1007/978-981-10-7641-1_31
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