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On the Vulnerability of Graph Learning-based Collaborative Filtering.

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Bibliographic Details
Title: On the Vulnerability of Graph Learning-based Collaborative Filtering.
Authors: SENRONG XU, LIANGYUE LI, ZENAN LI, YUAN YAO, FENG XU, ZULONG CHEN, QUAN LU, HANGHANG TONG
Source: ACM Transactions on Information Systems; Oct2023, Vol. 41 Issue 4, p1-28, 28p
Abstract: The article delves into the vulnerability of Graph Learning-based Collaborative Filtering (GLCF) in recommender systems, particularly its susceptibility to adversarial attacks. It covers topics such as the development of an adversarial attack against GLCF, a defense mechanism to protect against these attacks, and extensive experiments validating the effectiveness of both attack and defense strategies.
Database: Complementary Index
Description
Abstract:The article delves into the vulnerability of Graph Learning-based Collaborative Filtering (GLCF) in recommender systems, particularly its susceptibility to adversarial attacks. It covers topics such as the development of an adversarial attack against GLCF, a defense mechanism to protect against these attacks, and extensive experiments validating the effectiveness of both attack and defense strategies.
ISSN:10468188
DOI:10.1145/3572834