Threats, Vulnerabilities, and Controls of Machine Learning Based
Systems: A Survey and Taxonomy

Threats, Vulnerabilities, and Controls of Machine Learning Based Systems: A Survey and Taxonomy

18 January 2023

Yusuke Kawamoto

Kazumasa Miyake

Papers citing "Threats, Vulnerabilities, and Controls of Machine Learning Based Systems: A Survey and Taxonomy"

10 / 10 papers shown

Title
A Survey of Machine Unlearning Thanh Tam Nguyen T. T. Huynh Phi Le Nguyen Alan Wee-Chung Liew Hongzhi Yin Quoc Viet Hung Nguyen MU 77 221 0 06 Sep 2022
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 290 1,814 0 14 Dec 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 225 676 0 19 Oct 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 196 358 0 24 Mar 2020
Machine Unlearning: Linear Filtration for Logit-based Classifiers Thomas Baumhauer Pascal Schöttle Matthias Zeppelzauer MU 104 130 0 07 Feb 2020
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples Xiaojun Jia Xingxing Wei Xiaochun Cao H. Foroosh AAML 61 264 0 30 Nov 2018
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy Tsui-Wei Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 108 138 0 29 Nov 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 228 1,835 0 03 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 284 5,835 0 08 Jul 2016