220 citations · 286 across the 6 of their papers we have counts for
7 papers
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks
Jiaming Mu, Binghui Wang, Qi Li +3
Graph Neural Networks (GNNs) have achieved state-of-the-art performance in various graph structure related tasks such as node classification and graph classification. However, GNNs…
Realtime Robust Malicious Traffic Detection via Frequency Domain Analysis
Chuanpu Fu, Qi Li, Meng Shen +1
Machine learning (ML) based malicious traffic detection is an emerging security paradigm, particularly for zero-day attack detection, which is complementary to existing rule based…
Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis
Fengting Li, Xuankai Liu, Xiaoli Zhang +3
Deep neural networks (DNNs) have been applied in a wide range of applications,e.g.,face recognition and image classification; however,they are vulnerable to adversarial examples. B…
Robust Attacks on Deep Learning Face Recognition in the Physical World
Meng Shen, Hao Yu, Liehuang Zhu +3
Deep neural networks (DNNs) have been increasingly used in face recognition (FR) systems. Recent studies, however, show that DNNs are vulnerable to adversarial examples, which can…
Off-Path TCP Exploits of the Mixed IPID Assignment
Xuewei Feng, Chuanpu Fu, Qi Li +2
In this paper, we uncover a new off-path TCP hijacking attack that can be used to terminate victim TCP connections or inject forged data into victim TCP connections by manipulating…
Removing Backdoor-Based Watermarks in Neural Networks with Limited Data
Xuankai Liu, Fengting Li, Bihan Wen +1
Deep neural networks have been widely applied and achieved great success in various fields. As training deep models usually consumes massive data and computational resources, tradi…