Robust online filter recommended algorithm based on attack profile
Gao Feng · International Journal of Security and Its Applications · 2014
In view of the high vulnerability of traditional user-based recommendation algorithm to shilling attacks, In this paper, on the basis of the work of the group effect on the attack profiles, this paper analyzes the statistical features of the nearest neighbors of target users before and after attack, Design a kind of Attack Profiles online filter to attack the target user profile from the nearest neighbor filter.And this filter improves the user-based recommendation algorithm nearest neighbor selection strategy, thus proposes the Collaborative Recommendation algorithm based on Online Filter for Attack Profiles (CROFAP).Experiments show that attack profile online filter can accurately identify and filter out most attacks profile to ensure the robustness of the CROFAP algorithm.