activity
20192025
most citedRealtime Robust Malicious Traffic Detection via Frequency Domain Analysis

220 citations · 326 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2025

FlowletFormer: Network Behavioral Semantic Aware Pre-training Model for Traffic Classification

Liming Liu, Ruoyu Li, Qing Li +3

Network traffic classification using pre-training models has shown promising results, but existing methods struggle to capture packet structural characteristics, flow-level behavio…

cs.LG2021★ 2 cited

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…

cs.CR2021★ 220 cited

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…

cs.CV2021★ 5 cited

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…

cs.CV2020★ 1 cited

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…

cs.CR2020★ 37 cited

When the Differences in Frequency Domain are Compensated: Understanding and Defeating Modulated Replay Attacks on Automatic Speech Recognition

Shu Wang, Jiahao Cao, Xu He +2

Automatic speech recognition (ASR) systems have been widely deployed in modern smart devices to provide convenient and diverse voice-controlled services. Since ASR systems are vuln…

cs.CR2020★ 41 cited

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…

cs.CV2020★ 17 cited

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…

cs.NI2019★ 3 cited

Two Dimensional Router: Design and Implementation

Shu Yang, Laizhong Cui, Xinhao Deng +5

Higher dimensional classification has attracted more attentions with increasing demands for more flexible services in the Internet. In this paper, we present the design and impleme…