132 citations · 443 across the 43 of their papers we have counts for
9 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
Open DNN Box by Power Side-Channel Attack
Yun Xiang, Zhuangzhi Chen, Zuohui Chen +7
Deep neural networks are becoming popular and important assets of many AI companies. However, recent studies indicate that they are also vulnerable to adversarial attacks. Adversar…
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…