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Privacy-Preserving Demographic Filtering Alambic Management System

M. Sai, R. Srinivas, V.Sree Rekha

Abstract


The recommender systems are used as a way to user choices that needs to solve the protection problem in e-commerce. For solving such a problem we need to protect the privacy interests of users by hiding their identity and demographic features such as age, sex, geographical location, wealth, level of education, etc. and sometimes users buying preferences along with behavior. An E-commerce service provider allow commercial interests of users to protect data by recommending not to reveal valuable information that is related to market trends to the third parties. This paper concentrates only on recommender system that depends on demographic filtering which is familiar by making recommendations on feedback of previous users. The proposed system is called LAMBIC which is used to improve the privacy protection depending on semi-trusted third party by attaining limited confidence using such recommender systems. The process is to split the user’s data between the service provider and the third party in such a way that neither of them share the private data and protect it by preserving using demographic filtering.

Keywords


Recommender system, E-Commerce, LAMBIC, privacy protection, semi-trusted third party, demographic filtering.

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