Adaptive Attractors: A Defense Strategy against ML Adversarial Collusion Attacks
Authors: Jiyi Zhang, Han Fang, Ee-Chien Chang | Published: 2023-06-02
攻撃の評価
Certifiable Black-Box Attacks with Randomized Adversarial Examples: Breaking Defenses with Provable Confidence
Authors: Hanbin Hong, Xinyu Zhang, Binghui Wang, Zhongjie Ba, Yuan Hong | Published: 2023-04-10 | Updated: 2024-09-06
Does Prompt-Tuning Language Model Ensure Privacy?
Authors: Shangyu Xie, Wei Dai, Esha Ghosh, Sambuddha Roy, Dan Schwartz, Kim Laine | Published: 2023-04-07 | Updated: 2023-04-15
Adversarial Machine Learning-Based Anticipation of Threats Against Vehicle-to-Microgrid Services
Authors: Ahmed Omara, Burak Kantarci | Published: 2022-08-09
On False Data Injection Attack against Building Automation Systems
Authors: Michael Cash, Christopher Morales-Gonzalez, Shan Wang, Xipeng Jin, Alex Parlato, Jason Zhu, Qun Zhou Sun, Xinwen Fu | Published: 2022-08-04 | Updated: 2022-09-25
Logic Locking at the Frontiers of Machine Learning: A Survey on Developments and Opportunities
Authors: Dominik Sisejkovic, Lennart M. Reimann, Elmira Moussavi, Farhad Merchant, Rainer Leupers | Published: 2021-07-05 | Updated: 2021-11-23
Machine Learning for Network-based Intrusion Detection Systems: an Analysis of the CIDDS-001 Dataset
Authors: José Carneiro, Nuno Oliveira, Norberto Sousa, Eva Maia, Isabel Praça | Published: 2021-07-02
Gradient-Free Adversarial Attacks for Bayesian Neural Networks
Authors: Matthew Yuan, Matthew Wicker, Luca Laurenti | Published: 2020-12-23
Asymptotic Behavior of Adversarial Training in Binary Classification
Authors: Hossein Taheri, Ramtin Pedarsani, Christos Thrampoulidis | Published: 2020-10-26 | Updated: 2021-07-14
Erratum Concerning the Obfuscated Gradients Attack on Stochastic Activation Pruning
Authors: Guneet S. Dhillon, Nicholas Carlini | Published: 2020-09-30