activity
20182024
most citedFast Gradient Attack on Network Embedding

132 citations · 269 across the 33 of their papers we have counts for

collaborators
Showing cs.CRShow all

10 papers · 1 filter

cs.CR2024

DM4Steal: Diffusion Model For Link Stealing Attack On Graph Neural Networks

Jinyin Chen, Haonan Ma, Haibin Zheng

Graph has become increasingly integral to the advancement of recommendation systems, particularly with the fast development of graph neural network(GNN). By exploring the virtue of…

cs.CR2023

AIR: Threats of Adversarial Attacks on Deep Learning-Based Information Recovery

Jinyin Chen, Jie Ge, Shilian Zheng +5

A wireless communications system usually consists of a transmitter which transmits the information and a receiver which recovers the original information from the received distorte…

cs.CR2023

AdvCheck: Characterizing Adversarial Examples via Local Gradient Checking

Ruoxi Chen, Haibo Jin, Jinyin Chen +1

Deep neural networks (DNNs) are vulnerable to adversarial examples, which may lead to catastrophe in security-critical domains. Numerous detection methods are proposed to character…

cs.CR2023

Edge Deep Learning Model Protection via Neuron Authorization

Jinyin Chen, Haibin Zheng, Tao Liu +4

With the development of deep learning processors and accelerators, deep learning models have been widely deployed on edge devices as part of the Internet of Things. Edge device mod…

cs.CR2023

FedRight: An Effective Model Copyright Protection for Federated Learning

Jinyin Chen, Mingjun Li, Haibin Zheng

Federated learning (FL), an effective distributed machine learning framework, implements model training and meanwhile protects local data privacy. It has been applied to a broad va…

cs.CR2022★ 2 cited

GAIL-PT: A Generic Intelligent Penetration Testing Framework with Generative Adversarial Imitation Learning

Jinyin Chen, Shulong Hu, Haibin Zheng +2

Penetration testing (PT) is an efficient network testing and vulnerability mining tool by simulating a hacker's attack for valuable information applied in some areas. Compared with…

cs.CR2021★ 1 cited

CatchBackdoor: Backdoor Detection via Critical Trojan Neural Path Fuzzing

Haibo Jin, Ruoxi Chen, Jinyin Chen +3

The success of deep neural networks (DNNs) in real-world applications has benefited from abundant pre-trained models. However, the backdoored pre-trained models can pose a signific…

cs.CR2021★ 2 cited

TEGDetector: A Phishing Detector that Knows Evolving Transaction Behaviors

Jinyin Chen, Haiyang Xiong, Dunjie Zhang +2

Recently, phishing scams have posed a significant threat to blockchains. Phishing detectors direct their efforts in hunting phishing addresses. Most of the detectors extract target…

cs.CR2021★ 3 cited

DeepPoison: Feature Transfer Based Stealthy Poisoning Attack

Jinyin Chen, Longyuan Zhang, Haibin Zheng +2

Deep neural networks are susceptible to poisoning attacks by purposely polluted training data with specific triggers. As existing episodes mainly focused on attack success rate wit…

cs.CR2019★ 78 cited

POBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm

Jinyin Chen, Mengmeng Su, Shijing Shen +2

Most deep learning models are easily vulnerable to adversarial attacks. Various adversarial attacks are designed to evaluate the robustness of models and develop defense model. Cur…