Computer Science – Cryptography and Security
Scientific paper
2009-08-07
International Journal of Computer Science and Information Security, IJCSIS, Volume 3, Number 1, July 2009, USA
Computer Science
Cryptography and Security
6 Pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS July 2009, ISSN 1947 5500, Imp
Scientific paper
Secure Multi-Party Computation (SMC) allows parties with similar background to compute results upon their private data, minimizing the threat of disclosure. The exponential increase in sensitive data that needs to be passed upon networked computers and the stupendous growth of internet has precipitated vast opportunities for cooperative computation, where parties come together to facilitate computations and draw out conclusions that are mutually beneficial; at the same time aspiring to keep their private data secure. These computations are generally required to be done between competitors, who are obviously weary of each-others intentions. SMC caters not only to the needs of such parties but also provides plausible solutions to individual organizations for problems like privacy-preserving database query, privacy-preserving scientific computations, privacy-preserving intrusion detection and privacy-preserving data mining. This paper is an extension to a previously proposed protocol Encrytpo_Random, which presented a plain sailing yet effective approach to SMC and also put forward an aptly crafted architecture, whereby such an efficient protocol, involving the parties that have come forward for joint-computations and the third party who undertakes such computations, can be developed. Through this extended work an attempt has been made to further strengthen the existing protocol thus paving the way for a more secure multi-party computational process.
Bahety Ravish
Kapoor Nikhil
Koria Neha
Kumar Mishra Durgesh Dr.
No associations
LandOfFree
A Secure Multi-Party Computation Protocol for Malicious Computation Prevention for preserving privacy during Data Mining does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A Secure Multi-Party Computation Protocol for Malicious Computation Prevention for preserving privacy during Data Mining, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A Secure Multi-Party Computation Protocol for Malicious Computation Prevention for preserving privacy during Data Mining will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-152960