Research Article Open Access

Review on Generating Private Recommendations Using Elgamal Homomorphic Encryption

Abstract

User’s private or sensitive data can be misused because of curious administrators in online applications. Traditional ways of protecting data involve security of user’s privacy against third party but not from the service provider. To protect user’s data we present an encryption technique and generate recommendations. Recommendations are generated by processing data under encryption. Generating recommendations have become an important research area for the purpose of user’s privacy. By introducing a multiparty computation technique (MPC) the active participation of user can be eliminated, system can secure user’s private data and by comparing similarities generate recommendations.

Swapnali B. Swami, Soniya N. Madavi

To read the full article Download Full Article | Visit Full Article