• Manish Jaiswal
• T.J. Siddiqui

Recommender system is information filtering tools for handling the problem of information overwhelming. On the other side, security and protection is the prime concern for recommender system in order to provide genuine recommendation to the end users. Many e-commerce companies face attacks from malicious users who produce wrong recommendations to their buyers. Here, we presented the recommender system approaches, basic principles and overview of the different category of attacks discussed. In this work, we proposed a framework for genuine recommendation to users by detection of fake profile using correlation techniques based on correlation. Applicability of the proposed work in others domain with new techniques has been discussed in conclusion and future scope.

Recommender system, attack model, collaborative filtering, clustering

"A framework for securing Recommender Systems through Correlation techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.799-803, April-2019, Available :http://www.jetir.org/papers/JETIR1904V64.pdf

"A framework for securing Recommender Systems through Correlation techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp799-803, April-2019, Available at : http://www.jetir.org/papers/JETIR1904V64.pdf