Practical Data Poisoning Attack against Next-Item Recommendation

Some methods for classification and analysis of multivariate observations

James MacQueen et al · 1967

Earlier work this paper cites.

Residuals and influence in regression

R Dennis Cook and Sanford Weisberg. 1982 · 1982

Earlier work this paper cites.

Algorithms for non-negative matrix factorization. In Advances in Neural Information Processing Systems . 556–562

Daniel D Lee and H Sebastian Seung. 2001 · 2001

Earlier work this paper cites.

Shilling recommender systems for fun and profit. In Proceedings of the 13th international conference on World Wide Web . 393–402

Shyong K Lam and John Riedl. 2004 · 2004

Earlier work this paper cites.

Collaborative recommendation: A robustness analysis

Michael O’Mahony, Neil Hurley, Nicholas Kushmerick, and Guénolé Silvestre. 2004 · 2004

Earlier work this paper cites.

Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness

Bamshad Mobasher, Robin Burke, Runa Bhaumik, and Chad Williams. 2007 · 2007

Earlier work this paper cites.

BPR: Bayesian personalized ranking from implicit feedback. In Proceedings of the twenty-fifth conference on uncertainty in artificial intelligence . 452–461

Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009 · 2009

Earlier work this paper cites.

Factorizing personalized markov chains for next-basket recommendation. In Proceedings of the 19th international conference on World Wide Web . 811–820

Steffen Rendle, Christoph Freudenthaler, and Lars Schmidt-Thieme. 2010 · 2010

Earlier work this paper cites.

Poisoning attacks against support vector machines

Original

Battista Biggio, Blaine Nelson, and Pavel Laskov. 2012 · 2012

Cited alongside, same era.

Evasion attacks against machine learning at test time. In Joint European conference on machine learning and knowledge discovery in databases . Springer, 387–402

Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Šrndić, Pavel Laskov, Giorgio Giacinto, and Fabio Roli. 2013 · 2013

Cited alongside, same era.

The security of latent dirichlet allocation. In Artificial Intelligence and Statistics . 681–689

Shike Mei and Xiaojin Zhu. 2015 · 2015

Cited alongside, same era.

Data poisoning attacks against autoregressive models. In Thirtieth AAAI Conference on Artificial Intelligence

Scott Alfeld, Xiaojin Zhu, and Paul Barford. 2016 · 2016

Cited alongside, same era.

Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering. In proceedings of the 25th international conference on world wide web . 507–517

Towards poisoning of deep learning algorithms with back-gradient optimization. In Proc. of the 10th ACM Workshop on Artificial Intelligence and Security . 27–38

Luis Muñoz-González, Battista Biggio, Ambra Demontis, Andrea Paudice, Vasin Wongrassamee, Emil C Lupu, and Fabio Roli. 2017 · 2017

Later among the works it cites.

Practical black-box attacks against machine learning. In Proceedings of the 2017 ACM on Asia conference on computer and communications security . 506–519

Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z Berkay Celik, and Ananthram Swami. 2017 · 2017

Later among the works it cites.

Fake Co-visitation Injection Attacks to Recommender Systems.. In Proceedings of Network and Distributed System Security Symposium, 2017

Guolei Yang, Neil Zhenqiang Gong, and Ying Cai. 2017 · 2017

Later among the works it cites.

Self-attentive sequential recommendation. In Proceedings of the 2018 IEEE International Conference on Data Mining . 197–206

Wang-Cheng Kang and Julian McAuley. 2018 · 2018

Later among the works it cites.