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Data poisoning attacks spoof a recommender system to make arbitrary, attacker-desired recommendations via injecting fake users with carefully crafted rating scores into the recommender system.
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Leo Breiman · 1996
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Item-based collaborative filtering recommendation algorithms
Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl · 2001
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Amazon. com recommendations: Item-to-item collaborative filtering
Greg Linden, Brent Smith, and Jeremy York · 2003
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Shyong K Lam and John Riedl · 2004
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Segment-based injection attacks against collaborative filtering recommender systems
Robin Burke, Bamshad Mobasher, Runa Bhaumik, and Chad Williams · 2005
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Classification features for attack detection in collaborative recommender systems
Robin Burke, Bamshad Mobasher, Chad Williams, and Runa Bhaumik · 2006
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Attack detection in time series for recommender systems
Sheng Zhang, Amit Chakrabarti, James Ford, and Fillia Makedon · 2006
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Robust collaborative filtering
Bhaskar Mehta, Thomas Hofmann, and Wolfgang Nejdl · 2007
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Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness
Bamshad Mobasher, Robin Burke, Runa Bhaumik, and Chad Williams · 2007
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Robustness of collaborative recommendation based on association rule mining
Jeff J Sandvig, Bamshad Mobasher, and Robin Burke · 2007
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Collaborative filtering via ensembles of matrix factorizations
Mingrui Wu · 2007
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The bellkor 2008 solution to the netflix prize
Robert M Bell, Yehuda Koren, and Chris Volinsky · 2008
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Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky · 2009
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The bigchaos solution to the netflix grand prize
Andreas Töscher, Michael Jahrer, and Robert M Bell · 2009
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Bpr: Bayesian personalized ranking from implicit feedback
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme · 2012
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Hysad: A semi-supervised hybrid shilling attack detector for trustworthy product recommendation
Zhiang Wu, Junjie Wu, Jie Cao, and Dacheng Tao · 2012
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Trafficking fraudulent accounts: The role of the underground market in twitter spam and abuse
Kurt Thomas, Damon McCoy, Chris Grier, Alek Kolcz, and Vern Paxson · 2013
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Attacking item-based recommender systems with power items
Carlos E Seminario and David C Wilson · 2014
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Adversarial collaborative neural network for robust recommendation
Feng Yuan, Lina Yao, and Boualem Benatallah · 2019
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Microsoft recommenders: Best practices for production-ready recommendation systems
Andreas Argyriou, Miguel González-Fierro, and Le Zhang · 2020
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Influence function based data poisoning attacks to top-n recommender systems
Minghong Fang, Neil Zhenqiang Gong, and Jia Liu · 2020
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Lightgcn: Simplifying and powering graph convolution network for recommendation
Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, and Meng Wang · 2020
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Recommender systems robust to data poisoning using trim learning
Seira Hidano and Shinsaku Kiyomoto · 2020
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Certifiable robustness to discrete adversarial perturbations for factorization machines
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Hht–svm: An online method for detecting profile injection attacks in collaborative recommender systems
Fuzhi Zhang and Quanqiang Zhou · 2014
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2015
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The movielens datasets: History and context
F Maxwell Harper and Joseph A Konstan · 2015
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Data poisoning attacks on factorization-based collaborative filtering
Bo Li, Yining Wang, Aarti Singh, and Yevgeniy Vorobeychik · 2016
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Neural collaborative filtering
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua · 2017
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Fake co-visitation injection attacks to recommender systems
Guolei Yang, Neil Zhenqiang Gong, and Ying Cai · 2017
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Poisoning attacks to graph-based recommender systems
Minghong Fang, Guolei Yang, Neil Zhenqiang Gong, and Jia Liu · 2018
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Yang Liu, Xianzhuo Xia, Liang Chen, Xiangnan He, Carl Yang, and Zibin Zheng · 2020
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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 · 2020
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Revisiting adversarially learned injection attacks against recommender systems
Jiaxi Tang, Hongyi Wen, and Ke Wang · 2020
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Data poisoning attacks against differentially private recommender systems
Soumya Wadhwa, Saurabh Agrawal, Harsh Chaudhari, Deepthi Sharma, and Kannan Achan · 2020
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Practical data poisoning attack against next-item recommendation
Hengtong Zhang, Yaliang Li, Bolin Ding, and Jing Gao · 2020
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Data poisoning attacks to deep learning based recommender systems
Hai Huang, Jiaming Mu, Neil Zhenqiang Gong, Qi Li, Bin Liu, and Mingwei Xu · 2021
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Intrinsic certified robustness of bagging against data poisoning attacks
Jinyuan Jia, Xiaoyu Cao, and Neil Zhenqiang Gong · 2021
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Triple adversarial learning for influence based poisoning attack in recommender systems
Chenwang Wu, Defu Lian, Yong Ge, Zhihao Zhu, and Enhong Chen · 2021
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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
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Certified robustness of nearest neighbors against data poisoning and backdoor attacks
Jinyuan Jia, Yupei Liu, Xiaoyu Cao, and Neil Zhenqiang Gong · 2022
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