60 citations · 307 across the 18 of their papers we have counts for
5 papers · 1 filter
Graph Mining for Cybersecurity: A Survey
Bo Yan, Cheng Yang, Chuan Shi +4
The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society. Securing cyberspace has become an utmost concern for o…
Arms Race in Adversarial Malware Detection: A Survey
Deqiang Li, Qianmu Li, Yanfang Ye +1
Malicious software (malware) is a major cyber threat that has to be tackled with Machine Learning (ML) techniques because millions of new malware examples are injected into cybersp…
A Framework for Enhancing Deep Neural Networks Against Adversarial Malware
Deqiang Li, Qianmu Li, Yanfang Ye +1
Machine learning-based malware detection is known to be vulnerable to adversarial evasion attacks. The state-of-the-art is that there are no effective defenses against these attack…
Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and AICS'2019 Challenge
Deqiang Li, Qianmu Li, Yanfang Ye +1
Malware continues to be a major cyber threat, despite the tremendous effort that has been made to combat them. The number of malware in the wild steadily increases over time, meani…
AiDroid: When Heterogeneous Information Network Marries Deep Neural Network for Real-time Android Malware Detection
Yanfang Ye, Shifu Hou, Lingwei Chen +5
The explosive growth and increasing sophistication of Android malware call for new defensive techniques that are capable of protecting mobile users against novel threats. In this p…