34 citations · 68 across the 4 of their papers we have counts for
4 papers
Scalable Attribution of Adversarial Attacks via Multi-Task Learning
Zhongyi Guo, Keji Han, Yao Ge +2
Deep neural networks (DNNs) can be easily fooled by adversarial attacks during inference phase when attackers add imperceptible perturbations to original examples, i.e., adversaria…
PAD: Towards Principled Adversarial Malware Detection Against Evasion Attacks
Deqiang Li, Shicheng Cui, Yun Li +3
Machine Learning (ML) techniques can facilitate the automation of malicious software (malware for short) detection, but suffer from evasion attacks. Many studies counter such attac…
Generative Adversarial Learning for Trusted and Secure Clustering in Industrial Wireless Sensor Networks
Liu Yang, Simon X. Yang, Yun Li +2
Traditional machine learning techniques have been widely used to establish the trust management systems. However, the scale of training dataset can significantly affect the securit…
Learning Task-aware Robust Deep Learning Systems
Keji Han, Yun Li, Xianzhong Long +1
Many works demonstrate that deep learning system is vulnerable to adversarial attack. A deep learning system consists of two parts: the deep learning task and the deep model. Nowad…