23 citations · 57 across the 7 of their papers we have counts for
4 papers · 1 filter
COPYCAT: Practical Adversarial Attacks on Visualization-Based Malware Detection
Aminollah Khormali, Ahmed Abusnaina, Songqing Chen +2
Despite many attempts, the state-of-the-art of adversarial machine learning on malware detection systems generally yield unexecutable samples. In this work, we set out to examine t…
Examining Adversarial Learning against Graph-based IoT Malware Detection Systems
Ahmed Abusnaina, Aminollah Khormali, Hisham Alasmary +4
The main goal of this study is to investigate the robustness of graph-based Deep Learning (DL) models used for Internet of Things (IoT) malware classification against Adversarial L…
Analyzing, Comparing, and Detecting Emerging Malware: A Graph-based Approach
Hisham Alasmary, Aminollah Khormali, Afsah Anwar +4
The growth in the number of Android and Internet of Things (IoT) devices has witnessed a parallel increase in the number of malicious software (malware), calling for new analysis a…
End-to-End Analysis of In-Browser Cryptojacking
Muhammad Saad, Aminollah Khormali, Aziz Mohaisen
In-browser cryptojacking involves hijacking the CPU power of a website's visitor to perform CPU-intensive cryptocurrency mining, and has been on the rise, with 8500% growth during…