Shilling Attack Detection Model for Recommender System Based on Memory Principle
Jiafei Liu · Jisuanji gongcheng · 2012
This paper proposes a shilling attack detection model for recommender system based on memory principle.By combining biological memory principle and mathematics statistics,it detects shilling attacks through the memory cell's characteristics.The characteristic memory database can update timely,so that costs of system are saved.Experimental result shows that the model improves the ability of detecting shilling attacks of recommender system.