42 citations · 207 across the 76 of their papers we have counts for
4 papers · 1 filter
Understanding and Rectifying Safety Perception Distortion in VLMs
Xiaohan Zou, Jian Kang, George Kesidis +1
Recent studies reveal that vision-language models (VLMs) become more susceptible to harmful requests and jailbreak attacks after integrating the vision modality, exhibiting greater…
Temporal-Distributed Backdoor Attack Against Video Based Action Recognition
Xi Li, Songhe Wang, Ruiquan Huang +2
Deep neural networks (DNNs) have achieved tremendous success in various applications including video action recognition, yet remain vulnerable to backdoor attacks (Trojans). The ba…
L-RED: Efficient Post-Training Detection of Imperceptible Backdoor Attacks without Access to the Training Set
Zhen Xiang, David J. Miller, George Kesidis
Backdoor attacks (BAs) are an emerging form of adversarial attack typically against deep neural network image classifiers. The attacker aims to have the classifier learn to classif…
When Not to Classify: Detection of Reverse Engineering Attacks on DNN Image Classifiers
Yujia Wang, David J. Miller, George Kesidis
This paper addresses detection of a reverse engineering (RE) attack targeting a deep neural network (DNN) image classifier; by querying, RE's aim is to discover the classifier's de…