Wild Patterns Reloaded: A Survey of Machine Learning Security against
Training Data Poisoning

Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning

4 May 2022

Antonio Emanuele Cinà

Ambra Demontis

Sebastiano Vascon

Werner Zellinger

Bernhard A. Moser

Battista Biggio

Marcello Pelillo

Fabio Roli

Papers citing "Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning"

19 / 19 papers shown

Title
Artificial Intelligence health advice accuracy varies across languages and contexts Prashant Garg Thiemo Fetzer 42 0 0 25 Apr 2025
Statistically Testing Training Data for Unwanted Error Patterns using Rule-Oriented Regression Stefan Rass Martin Dallinger 38 0 0 24 Mar 2025
Position: A taxonomy for reporting and describing AI security incidents L. Bieringer Kevin Paeth Andreas Wespi Kathrin Grosse Alexandre Alahi Kathrin Grosse 78 0 0 19 Dec 2024
Human-inspired Perspectives: A Survey on AI Long-term Memory Zihong He Weizhe Lin Hao Zheng Fan Zhang Matt Jones Laurence Aitchison X. Xu Miao Liu Per Ola Kristensson Junxiao Shen 67 2 0 01 Nov 2024
Timber! Poisoning Decision Trees Stefano Calzavara Lorenzo Cazzaro Massimo Vettori AAML 23 0 0 01 Oct 2024
Machine Unlearning Fails to Remove Data Poisoning Attacks Martin Pawelczyk Jimmy Z. Di Yiwei Lu Gautam Kamath Ayush Sekhari Seth Neel AAML MU 50 7 0 25 Jun 2024
Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems Guangjing Wang Ce Zhou Yuanda Wang Bocheng Chen Hanqing Guo Qiben Yan AAML SILM 41 3 0 20 Nov 2023
Minimizing Energy Consumption of Deep Learning Models by Energy-Aware Training Dario Lazzaro Antonio Emanuele Cinà Maura Pintor Ambra Demontis Battista Biggio Fabio Roli Marcello Pelillo 17 6 0 01 Jul 2023
A Proxy Attack-Free Strategy for Practically Improving the Poisoning Efficiency in Backdoor Attacks Ziqiang Li Hong Sun Pengfei Xia Beihao Xia Xue Rui Wei Zhang Qinglang Guo Bin Li AAML 25 8 0 14 Jun 2023
On the Limitations of Model Stealing with Uncertainty Quantification Models David Pape Sina Daubener Thorsten Eisenhofer Antonio Emanuele Cinà Lea Schonherr 9 3 0 09 May 2023
Machine Learning Security in Industry: A Quantitative Survey Kathrin Grosse L. Bieringer Tarek R. Besold Battista Biggio Katharina Krombholz 19 31 0 11 Jul 2022
On Collective Robustness of Bagging Against Data Poisoning Ruoxin Chen Zenan Li Jie Li Chentao Wu Junchi Yan 40 23 0 26 May 2022
Energy-Latency Attacks via Sponge Poisoning Antonio Emanuele Cinà Ambra Demontis Battista Biggio Fabio Roli Marcello Pelillo SILM 37 27 0 14 Mar 2022
Regularization Can Help Mitigate Poisoning Attacks... with the Right Hyperparameters Javier Carnerero-Cano Luis Muñoz-González P. Spencer Emil C. Lupu AAML 16 10 0 23 May 2021
Mitigating backdoor attacks in LSTM-based Text Classification Systems by Backdoor Keyword Identification Chuanshuai Chen Jiazhu Dai SILM 48 126 0 11 Jul 2020
Clean-Label Backdoor Attacks on Video Recognition Models Shihao Zhao Xingjun Ma Xiang Zheng James Bailey Jingjing Chen Yu-Gang Jiang AAML 176 252 0 06 Mar 2020
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 162 284 0 02 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 174 1,014 0 29 Nov 2018
Bilevel Programming for Hyperparameter Optimization and Meta-Learning Luca Franceschi P. Frasconi Saverio Salzo Riccardo Grazzi Massimiliano Pontil 96 714 0 13 Jun 2018