Sensitivity Context Awareness based Privacy Preserving Recommender System

Abstract

The Recommender Systems plays a vital role in today’s Business World. To deliver beneficial recommendations on various products to the consumers is a core objective of the custom-made recommendation system. The recommendations service requires several types of consumer data like earlier product purchased details, consumer information, demographics, and realistic details. The consumers also called Data Providers are prone to the revelation of individual information. This information will be distorted/misused by attackers or malicious third party Data Analyzer. To defend against personal information privacy breaches, it is necessary to modify the consumer information using a privacy preservation technique and generate recommendations by building correct information. The malicious third party and/or Data Analyst of organization not able to access/alter data which will be used for recommendation. Our proposed Sensitivity Context Awareness based Privacy Preserving Recommender System mainly focuses on consumer consent to publish data for the recommendation and at same time conserves privacy of consumers and utility of data which will be used to generate recommendation.