A Review of Various Datasets for Machine Learning Algorithm-Based Intrusion Detection System: Advances and Challenges
Authors: Sudhanshu Sekhar Tripathy, Bichitrananda Behera | Published: 2025-06-03
Trigger Detection
Toward Malicious Clients Detection in Federated Learning
Authors: Zhihao Dou, Jiaqi Wang, Wei Sun, Zhuqing Liu, Minghong Fang | Published: 2025-05-14
Bayesian Robust Aggregation for Federated Learning
Authors: Aleksandr Karakulev, Usama Zafar, Salman Toor, Prashant Singh | Published: 2025-05-05
LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors
Authors: Chengkun Wei, Wenlong Meng, Zhikun Zhang, Min Chen, Minghu Zhao, Wenjing Fang, Lei Wang, Zihui Zhang, Wenzhi Chen | Published: 2023-08-26 | Updated: 2023-10-14
ONION: A Simple and Effective Defense Against Textual Backdoor Attacks
Authors: Fanchao Qi, Yangyi Chen, Mukai Li, Yuan Yao, Zhiyuan Liu, Maosong Sun | Published: 2020-11-20 | Updated: 2021-11-03
Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks
Authors: Aditya Golatkar, Alessandro Achille, Stefano Soatto | Published: 2019-11-12 | Updated: 2020-03-31
Februus: Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems
Authors: Bao Gia Doan, Ehsan Abbasnejad, Damith C. Ranasinghe | Published: 2019-08-09 | Updated: 2020-09-28
Scaling up the randomized gradient-free adversarial attack reveals overestimation of robustness using established attacks
Authors: Francesco Croce, Jonas Rauber, Matthias Hein | Published: 2019-03-27 | Updated: 2019-09-25
STRIP: A Defence Against Trojan Attacks on Deep Neural Networks
Authors: Yansong Gao, Chang Xu, Derui Wang, Shiping Chen, Damith C. Ranasinghe, Surya Nepal | Published: 2019-02-18 | Updated: 2020-01-17
Discretization based Solutions for Secure Machine Learning against Adversarial Attacks
Authors: Priyadarshini Panda, Indranil Chakraborty, Kaushik Roy | Published: 2019-02-08 | Updated: 2019-02-11