SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks
Authors: Alexander Robey, Eric Wong, Hamed Hassani, George J. Pappas | Published: 2023-10-05 | Updated: 2024-06-11
Defense Method
Breaking On-Chip Communication Anonymity using Flow Correlation Attacks
Authors: Hansika Weerasena, Prabhat Mishra | Published: 2023-09-27 | Updated: 2025-05-06
How Robust is Google’s Bard to Adversarial Image Attacks?
Authors: Yinpeng Dong, Huanran Chen, Jiawei Chen, Zhengwei Fang, Xiao Yang, Yichi Zhang, Yu Tian, Hang Su, Jun Zhu | Published: 2023-09-21 | Updated: 2023-10-14
Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM
Authors: Bochuan Cao, Yuanpu Cao, Lu Lin, Jinghui Chen | Published: 2023-09-18 | Updated: 2024-06-12
DAD++: Improved Data-free Test Time Adversarial Defense
Authors: Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty | Published: 2023-09-10
Adversarially Robust Deep Learning with Optimal-Transport-Regularized Divergences
Authors: Jeremiah Birrell, Mohammadreza Ebrahimi | Published: 2023-09-07
Protect Federated Learning Against Backdoor Attacks via Data-Free Trigger Generation
Authors: Yanxin Yang, Ming Hu, Yue Cao, Jun Xia, Yihao Huang, Yang Liu, Mingsong Chen | Published: 2023-08-22
A Review of Adversarial Attacks in Computer Vision
Authors: Yutong Zhang, Yao Li, Yin Li, Zhichang Guo | Published: 2023-08-15
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection
Authors: João Vitorino, Isabel Praça, Eva Maia | Published: 2023-08-13
Pelta: Shielding Transformers to Mitigate Evasion Attacks in Federated Learning
Authors: Simon Queyrut, Yérom-David Bromberg, Valerio Schiavoni | Published: 2023-08-08