Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack

22 July 2021

Papers citing "Ready for Emerging Threats to Recommender Systems? A Graph Convolution-based Generative Shilling Attack"

8 / 8 papers shown

Title
Poisoning Attacks and Defenses in Recommender Systems: A Survey Zongwei Wang Junliang Yu Min Gao Wei Yuan Guanhua Ye S. Sadiq Hongzhi Yin AAML 43 6 0 03 Jun 2024
Towards Robust Recommendation: A Review and an Adversarial Robustness Evaluation Library Lei Cheng Xiaowen Huang Jitao Sang Jian Yu AAML 25 1 0 27 Apr 2024
Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures Thanh Toan Nguyen Quoc Viet Hung Nguyen Thanh Tam Nguyen T. T. Huynh Thanh Thi Nguyen Matthias Weidlich Hongzhi Yin AAML 21 21 0 23 Apr 2024
Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks Zongwei Wang Junliang Yu Min Gao Hongzhi Yin Bin Cui S. Sadiq AAML 26 7 0 30 Nov 2023
The GANfather: Controllable generation of malicious activity to improve defence systems Ricardo Pereira Jacopo Bono João Tiago Ascensão David Oliveira Aparício Pedro Ribeiro P. Bizarro AAML 21 2 0 25 Jul 2023
Towards Adversarially Robust Recommendation from Adaptive Fraudster Detection Y. Lai Yulin Zhu Wenqi Fan Xiaoge Zhang Kai Zhou AAML 24 4 0 08 Nov 2022
Efficient Bi-Level Optimization for Recommendation Denoising Zongwei Wang Min Gao Wentao Li Junliang Yu Linxin Guo Hongzhi Yin 11 27 0 19 Oct 2022
Discussion about Attacks and Defenses for Fair and Robust Recommendation System Design Mira Kim Simon S. Woo 14 0 0 28 Sep 2022