Link farm, an effective attack to Page Rank in algorithm in graph-based recommender systems

Document Type : Persian Original Article

Authors

School of Computer Engineering, Yazd University, Yazd, Iran.

Abstract

Nowadays recommender systems have become an integral part of e-commerce websites. However the general and accessibility of these systems has made them vulnerable to attack by profiteering users. Numerous studies have examined the vulnerability of various recommender algorithms to attacks created by creating fake profiles, many of which have focused on older methods, including group refinement algorithms.
A group of recommender algorithms considered by various Internet services use a variety of graph analysis methods, including random steps, to provide suggestions to the user. There are limited studies on the vulnerability of graph-based recommender algorithms that focus on specific types of these methods. Therefore, in this paper, the vulnerability of a group of graph-based algorithms that use the idea of ​​PageRank ranking algorithm on the web to score items and generate their suggestions was examined.
To do this, a new attack model called the link farm is proposed using the PageRank ranking algorithm applied. The results obtained from the application of different attacks to these techniques have shown that the proposed attack model affects this group of graph-based recommender algorithms.

Keywords

References

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Journal of Soft Computing and Information Technology
Volume 10, Issue 2 - Serial Number 32
Summer
July 2021
Pages 53-67

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