8 citations · 17 across the 9 of their papers we have counts for
7 papers · 1 filter
ML-based IoT Malware Detection Under Adversarial Settings: A Systematic Evaluation
Ahmed Abusnaina, Afsah Anwar, Sultan Alshamrani +4
The rapid growth of the Internet of Things (IoT) devices is paralleled by them being on the front-line of malicious attacks. This has led to an explosion in the number of IoT malwa…
ShellCore: Automating Malicious IoT Software Detection by Using Shell Commands Representation
Hisham Alasmary, Afsah Anwar, Ahmed Abusnaina +6
The Linux shell is a command-line interpreter that provides users with a command interface to the operating system, allowing them to perform a variety of functions. Although very u…
Cleaning the NVD: Comprehensive Quality Assessment, Improvements, and Analyses
Afsah Anwar, Ahmed Abusnaina, Songqing Chen +2
Vulnerability databases are vital sources of information on emergent software security concerns. Security professionals, from system administrators to developers to researchers, he…
A Deep Learning-based Fine-grained Hierarchical Learning Approach for Robust Malware Classification
Ahmed Abusnaina, Mohammed Abuhamad, Hisham Alasmary +5
The wide acceptance of Internet of Things (IoT) for both household and industrial applications is accompanied by several security concerns. A major security concern is their probab…
Sensor-based Continuous Authentication of Smartphones' Users Using Behavioral Biometrics: A Contemporary Survey
Mohammed Abuhamad, Ahmed Abusnaina, DaeHun Nyang +1
Mobile devices and technologies have become increasingly popular, offering comparable storage and computational capabilities to desktop computers allowing users to store and intera…
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…