4 papers
NADD: Amplifying Noise for Effective Diffusion-based Adversarial Purification
David D. Nguyen, The-Anh Ta, Yansong Gao +1
The strategy of combining diffusion-based generative models with classifiers continues to demonstrate state-of-the-art performance on adversarial robustness benchmarks. Known as ad…
Large Language Model Adversarial Landscape Through the Lens of Attack Objectives
Nan Wang, Kane Walter, Yansong Gao +1
Large Language Models (LLMs) represent a transformative leap in artificial intelligence, enabling the comprehension, generation, and nuanced interaction with human language on an u…
Comprehensive Evaluation of Cloaking Backdoor Attacks on Object Detector in Real-World
Hua Ma, Alsharif Abuadbba, Yansong Gao +2
The exploration of backdoor vulnerabilities in object detectors, particularly in real-world scenarios, remains limited. A significant challenge lies in the absence of a natural phy…
From Solitary Directives to Interactive Encouragement! LLM Secure Code Generation by Natural Language Prompting
Shigang Liu, Bushra Sabir, Seung Ick Jang +5
Large Language Models (LLMs) have shown remarkable potential in code generation, making them increasingly important in the field. However, the security issues of generated code hav…