34 citations · 37 across the 3 of their papers we have counts for
3 papers
cs.LG2023
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…
cs.CR2023★ 34 cited
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…
cs.NI2022★ 3 cited
Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks
Liu Yang, Yun Li, Simon X. Yang +3
Emerging six generation (6G) is the integration of heterogeneous wireless networks, which can seamlessly support anywhere and anytime networking. But high Quality-of-Trust should b…