Fetching the paper…
Reading the bibliography…
Modern recommender systems (RS) have seen substantial success, yet they remain vulnerable to malicious activities, notably poisoning attacks.
Promoting recommendations: An attack on collaborative filtering
Michael P O’Mahony, Neil J Hurley, and Guenole CM Silvestre · 2002
Earlier work this paper cites.
Limited knowledge shilling attacks in collaborative filtering systems
Robin Burke, Bamshad Mobasher, and Runa Bhaumik · 2005
Earlier work this paper cites.
Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky · 2009
Earlier work this paper cites.
Shilling attacks against recommender systems: a comprehensive survey
Ihsan Gunes, Cihan Kaleli, Alper Bilge, and Huseyin Polat · 2014
Earlier work this paper cites.
Wide & deep learning for recommender systems
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, et al · 2016
Earlier work this paper cites.
Data poisoning attacks on factorization-based collaborative filtering
Bo Li, Yining Wang, Aarti Singh, and Yevgeniy Vorobeychik · 2016
Earlier work this paper cites.
Fake co-visitation injection attacks to recommender systems
Guolei Yang, Neil Zhenqiang Gong, and Ying Cai · 2017
Earlier work this paper cites.
Hybrid attacks on model-based social recommender systems
Junliang Yu, Min Gao, Wenge Rong, Wentao Li, Qingyu Xiong, and Junhao Wen · 2017
Earlier work this paper cites.
Poisoning attacks to graph-based recommender systems
Minghong Fang, Guolei Yang, Neil Zhenqiang Gong, and Jia Liu · 2018
Earlier work this paper cites.
Poison as a cure: Detecting & neutralizing variable-sized backdoor attacks in deep neural networks
Alvin Chan and Yew-Soon Ong · 2019
Earlier work this paper cites.
Data poisoning attacks on cross-domain recommendation
Huiyuan Chen and Jing Li · 2019
Earlier work this paper cites.
Adversarial attacks on an oblivious recommender
Christakopoulou, Konstantina, and Arindam Banerjee · 2019
Earlier work this paper cites.
Graph convolutional networks: a comprehensive review
Si Zhang, Hanghang Tong, Jiejun Xu, and Ross Maciejewski · 2019
Earlier work this paper cites.
Influence function based data poisoning attacks to top-n recommender systems
Minghong Fang, Neil Zhenqiang Gong, and Jia Liu · 2020
Earlier work this paper cites.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
Earlier work this paper cites.
Attacking recommender systems with augmented user profiles
Chen Lin, Si Chen, Hui Li, Yanghua Xiao, Lianyun Li, and Qian Yang · 2020
Earlier work this paper cites.
Shilling attacks against collaborative recommender systems: a review
Mingdan Si and Qingshan Li · 2020
Earlier work this paper cites.
Revisiting adversarially learned injection attacks against recommender systems
Jiaxi Tang, Hongyi Wen, and Ke Wang · 2020
Earlier work this paper cites.
Practical data poisoning attack against next-item recommendation
Hengtong Zhang, Yaliang Li, Bolin Ding, and Jing Gao · 2020
Earlier work this paper cites.
Gcn-based user representation learning for unifying robust recommendation and fraudster detection
Shijie Zhang, Hongzhi Yin, Tong Chen, Quoc Viet Nguyen Hung, Zi Huang, and Lizhen Cui · 2020
Earlier work this paper cites.
Towards poisoning the neural collaborative filtering-based recommender systems
Yihe Zhang, Jiadong Lou, Li Chen, Xu Yuan, Jin Li, Tom Johnsten, and Nian-Feng Tzeng · 2020
Earlier work this paper cites.
Adversarial recommender systems: Attack, defense, and advances
Vito Walter Anelli, Yashar Deldjoo, Tommaso DiNoia, and Felice Antonio Merra · 2021
Earlier work this paper cites.
Data poisoning attacks on neighborhood-based recommender systems
Liang Chen, Yangjun Xu, Fenfang Xie, Min Huang, and Zibin Zheng · 2021
Earlier work this paper cites.
A survey on adversarial recommender systems: from attack/defense strategies to generative adversarial networks
Yashar Deldjoo, Tommaso Di Noia, and Felice Antonio Merra · 2021
Cited alongside, same era.
Attacking black-box recommendations via copying cross-domain user profiles
Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, and Qing Li · 2021
Cited alongside, same era.
Data poisoning attacks to deep learning based recommender systems
Hai Huang, Jiaming Mu, Neil Zhenqiang Gong, Qi Li, Bin Liu, and Mingwei Xu · 2021
Cited alongside, same era.
A survey on knowledge graphs: Representation, acquisition, and applications
Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, and S Yu Philip · 2021
Cited alongside, same era.
Poisonrec: an adaptive data poisoning framework for attacking black-box recommender systems
Junshuai Song, Zhao Li, Zehong Hu, Yucheng Wu, Zhenpeng Li, Jian Li, and Jun Gao · 2021
Cited alongside, same era.
Attacking recommender systems with plausible profile
Xuxin Zhang, Jian Chen, Rui Zhang, Chen Wang, and Ling Liu · 2022
Later among the works it cites.
Adversarial item promotion on visually-aware recommender systems by guided diffusion
Lijian Chen, Wei Yuan, Tong Chen, and Hongzhi Yin · 2023
Later among the works it cites.
The dark side of explanations: Poisoning recommender systems with counterfactual examples
Ziheng Chen, Fabrizio Silvestri, Jia Wang, Yongfeng Zhang, and Gabriele Tolomei · 2023
Later among the works it cites.
Shilling black-box review-based recommender systems through fake review generation
Hung-Yun Chiang, Yi-Syuan Chen, Yun-Zhu Song, Hong-Han Shuai, and Jason S Chang · 2023
Later among the works it cites.
Adversarial attacks for black-box recommender systems via copying transferable cross-domain user profiles
Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, and Jiliang Tang · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Triple adversarial learning for influence based poisoning attack in recommender systems
Chenwang Wu, Defu Lian, Yong Ge, Zhihao Zhu, and Enhong Chen · 2021
Cited alongside, same era.
Fight fire with fire: towards robust recommender systems via adversarial poisoning training
Chenwang Wu, Defu Lian, Yong Ge, Zhihao Zhu, Enhong Chen, and Senchao Yuan · 2021
Cited alongside, same era.
Ready for emerging threats to recommender systems? a graph convolution-based generative shilling attack
Fan Wu, Min Gao, Junliang Yu, Zongwei Wang, Kecheng Liu, and Xu Wang · 2021
Cited alongside, same era.
Black-box attacks on sequential recommenders via data-free model extraction
Zhenrui Yue, Zhankui He, Huimin Zeng, and Julian McAuley · 2021
Cited alongside, same era.
Data poisoning attack against recommender system using incomplete and perturbed data
Hengtong Zhang, Changxin Tian, Yaliang Li, Lu Su, Nan Yang, Wayne Xin Zhao, and Jing Gao · 2021
Cited alongside, same era.
Reverse attack: Black-box attacks on collaborative recommendation
Yihe Zhang, Xu Yuan, Jin Li, Jiadong Lou, Li Chen, and Nian-Feng Tzeng · 2021
Cited alongside, same era.
Knowledge-enhanced black-box attacks for recommendations
Jingfan Chen, Wenqi Fan, Guanghui Zhu, Xiangyu Zhao, Chunfeng Yuan, Qing Li, and Yihua Huang · 2022
Cited alongside, same era.
Targeted shilling attacks on gnn-based recommender systems
Sihan Guo, Ting Bai, and Weihong Deng · 2023
Later among the works it cites.
Single-user injection for invisible shilling attack against recommender systems
Chengzhi Huang and Hui Li · 2023
Later among the works it cites.
Recad: Towards a unified library for recommender attack and defense
Changsheng Wang, Jianbai Ye, Wenjie Wang, Chongming Gao, Fuli Feng, and Xiangnan He · 2023
Later among the works it cites.
Poisoning self-supervised learning based sequential recommendations
Yanling Wang, Yuchen Liu, Qian Wang, Cong Wang, and Chenliang Li · 2023
Later among the works it cites.
Revisiting data poisoning attacks on deep learning based recommender systems
Zhiye Wang, Baisong Liu, Chennan Lin, Xueyuan Zhang, Ce Hu, Jiangcheng Qin, and Linze Luo · 2023
Later among the works it cites.
Efficient bi-level optimization for recommendation denoising
Zongwei Wang, Min Gao, Wentao Li, Junliang Yu, Linxin Guo, and Hongzhi Yin · 2023
Later among the works it cites.
Poisoning attacks against contrastive recommender systems
Zongwei Wang, Junliang Yu, Min Gao, Hongzhi Yin, Bin Cui, and Shazia Sadiq · 2023
Later among the works it cites.
Influence-driven data poisoning for robust recommender systems
Chenwang Wu, Defu Lian, Yong Ge, Zhihao Zhu, and Enhong Chen · 2023
Later among the works it cites.
A survey on large language models for recommendation
Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu, Qi Liu, et al · 2023
Later among the works it cites.
Attacking pre-trained recommendation
Yiqing Wu, Ruobing Xie, Zhao Zhang, Yongchun Zhu, FuZhen Zhuang, Jie Zhou, Yongjun Xu, and Qing He · 2023
Later among the works it cites.
Planning data poisoning attacks on heterogeneous recommender systems in a multiplayer setting
Chin-Yuan Yeh, Hsi-Wen Chen, De-Nian Yang, Wang-Chien Lee, S Yu Philip, and Ming-Syan Chen · 2023
Later among the works it cites.
Ua-fedrec: untargeted attack on federated news recommendation
Jingwei Yi, Fangzhao Wu, Bin Zhu, Jing Yao, Zhulin Tao, Guangzhong Sun, and Xing Xie · 2023
Later among the works it cites.
Self-supervised learning for recommender systems: A survey
Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Jundong Li, and Zi Huang · 2023
Later among the works it cites.
Untargeted attack against federated recommendation systems via poisonous item embeddings and the defense
Yang Yu, Qi Liu, Likang Wu, Runlong Yu, Sanshi Lei Yu, and Zaixi Zhang · 2023
Later among the works it cites.
Manipulating federated recommender systems: Poisoning with synthetic users and its countermeasures
Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen, and Hongzhi Yin · 2023
Later among the works it cites.
Where to go next for recommender systems? id-vs. modality-based recommender models revisited
Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, and Yongxin Ni · 2023
Later among the works it cites.
Practical cross-system shilling attacks with limited access to data
Meifang Zeng, Ke Li, Bingchuan Jiang, Liujuan Cao, and Hui Li · 2023
Later among the works it cites.