Survey Paper on Generating Customer Relationship Management Efficiently using Homomorphic Encryption and Data Packing

Abstract

In recommender systems, recommendations are generated based on the data collected from the user. The important requirement of the basic Information Filtering architectures is to protect the privacy of all the users. By using the Homomorphic encryption and data packing the recommender system provides good privacy of customer data. The data protection system gives security from malicious third parties, but does not provide security from the service provider. In this paper, our aim is to generate the dynamic recommendations and protect the confidential data of user against the service provider while protecting the functionality of the system. This system is very useful to generate dynamic recommendations by preserving the privacy of the users.