444 citations · 521 across the 6 of their papers we have counts for
7 papers · 1 filter
Mobile Botnet Detection: A Deep Learning Approach Using Convolutional Neural Networks
Suleiman Y. Yerima, Mohammed K. Alzaylaee
Android, being the most widespread mobile operating systems is increasingly becoming a target for malware. Malicious apps designed to turn mobile devices into bots that may form pa…
High Accuracy Phishing Detection Based on Convolutional Neural Networks
Suleiman Y. Yerima, Mohammed K. Alzaylaee
The persistent growth in phishing and the rising volume of phishing websites has led to individuals and organizations worldwide becoming increasingly exposed to various cyber-attac…
DL-Droid: Deep learning based android malware detection using real devices
Mohammed K. Alzaylaee, Suleiman Y. Yerima, Sakir Sezer
The Android operating system has been the most popular for smartphones and tablets since 2012. This popularity has led to a rapid raise of Android malware in recent years. The soph…
Continuous Implicit Authentication for Mobile Devices based on Adaptive Neuro-Fuzzy Inference System
Feng Yao, Suleiman Y. Yerima, BooJoong Kang +1
As mobile devices have become indispensable in modern life, mobile security is becoming much more important. Traditional password or PIN-like point-of-entry security measures score…
Improving Dynamic Analysis of Android Apps Using Hybrid Test Input Generation
Mohammed K. Alzaylaee, Suleiman Y. Yerima, Sakir Sezer
The Android OS has become the most popular mobile operating system leading to a significant increase in the spread of Android malware. Consequently, several static and dynamic anal…
EMULATOR vs REAL PHONE: Android Malware Detection Using Machine Learning
Mohammed K. Alzaylaee, Suleiman Y. Yerima, Sakir Sezer
The Android operating system has become the most popular operating system for smartphones and tablets leading to a rapid rise in malware. Sophisticated Android malware employ detec…