158 citations
3 papers
cs.CR2022★ 158 cited
Machine Learning for Encrypted Malicious Traffic Detection: Approaches, Datasets and Comparative Study
Zihao Wang, Kar-Wai Fok, Vrizlynn L. L. Thing
As people's demand for personal privacy and data security becomes a priority, encrypted traffic has become mainstream in the cyber world. However, traffic encryption is also shield…
cs.CR2021★ 6 cited
"How Does It Detect A Malicious App?" Explaining the Predictions of AI-based Android Malware Detector
Zhi Lu, Vrizlynn L. L. Thing
AI methods have been proven to yield impressive performance on Android malware detection. However, most AI-based methods make predictions of suspicious samples in a black-box manne…
cs.CR2021★ 109 cited
Three Decades of Deception Techniques in Active Cyber Defense -- Retrospect and Outlook
Li Zhang, Vrizlynn L. L. Thing
Deception techniques have been widely seen as a game changer in cyber defense. In this paper, we review representative techniques in honeypots, honeytokens, and moving target defen…