Privacy Preserving k Secure Sum Protocol

Abstract

Secure Multiparty Computation (SMC) allows parties to know the result of cooperative computation while preserving privacy of individual data. Secure sum computation is an important application of SMC. In our proposed protocols parties are allowed to compute the sum while keeping their individual data secret with increased computation complexity for hacking individual data. In this paper the data of individual party is broken into a fixed number of segments. For increasing the complexity we have used the randomization technique with segmentation

5 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS November 2009, ISSN 1947 5500, http://sites.google.com/site/ijcsis/

References in corpus (1)

• A Secure Multi-Party Computation Protocol for Malicious Computation Prevention for preserving privacy during Data Mining

Cited by in corpus (6)

• A Survey of Self-Sovereign Identity Ecosystem
• Data Aggregation without Secure Channel: How to Evaluate a Multivariate Polynomial Securely
• A Distributed k-Secure Sum Protocol for Secure Multi-Party Computations
• Changing Neighbors k Secure Sum Protocol for Secure Multi Party Computation
• A Modified ck-Secure Sum Protocol for Multi-Party Computation
• Experimental realization of secure multi-party computation in an entanglement access to network