ParaFuzz: An Interpretability-Driven Technique for Detecting Poisoned Samples in NLP
Authors: Lu Yan, Zhuo Zhang, Guanhong Tao, Kaiyuan Zhang, Xuan Chen, Guangyu Shen, Xiangyu Zhang | Published: 2023-08-04 | Updated: 2023-10-27
Poisoning
Security and Privacy Issues of Federated Learning
Authors: Jahid Hasan | Published: 2023-07-22
Mitigating Communications Threats in Decentralized Federated Learning through Moving Target Defense
Authors: Enrique Tomás Martínez Beltrán, Pedro Miguel Sánchez Sánchez, Sergio López Bernal, Gérôme Bovet, Manuel Gil Pérez, Gregorio Martínez Pérez, Alberto Huertas Celdrán | Published: 2023-07-21 | Updated: 2023-12-09
Rethinking Backdoor Attacks
Authors: Alaa Khaddaj, Guillaume Leclerc, Aleksandar Makelov, Kristian Georgiev, Hadi Salman, Andrew Ilyas, Aleksander Madry | Published: 2023-07-19
Defending Against Poisoning Attacks in Federated Learning with Blockchain
Authors: Nanqing Dong, Zhipeng Wang, Jiahao Sun, Michael Kampffmeyer, William Knottenbelt, Eric Xing | Published: 2023-07-02 | Updated: 2024-03-12
On the Exploitability of Instruction Tuning
Authors: Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, Tom Goldstein | Published: 2023-06-28 | Updated: 2023-10-28
Towards Sybil Resilience in Decentralized Learning
Authors: Thomas Werthenbach, Johan Pouwelse | Published: 2023-06-26
Boosting Model Inversion Attacks with Adversarial Examples
Authors: Shuai Zhou, Tianqing Zhu, Dayong Ye, Xin Yu, Wanlei Zhou | Published: 2023-06-24
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses
Authors: Mohamed Amine Ferrag, Othmane Friha, Burak Kantarci, Norbert Tihanyi, Lucas Cordeiro, Merouane Debbah, Djallel Hamouda, Muna Al-Hawawreh, Kim-Kwang Raymond Choo | Published: 2023-06-17 | Updated: 2024-02-08
Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks
Authors: Daniel Gibert, Jordi Planes, Quan Le, Giulio Zizzo | Published: 2023-06-16