Advancing cybersecurity: a comprehensive review of AI-driven detection techniques

AH Salem, SM Azzam, OE Emam, AA Abohany - Journal of Big Data, 2024 - Springer
As the number and cleverness of cyber-attacks keep increasing rapidly, it's more important
than ever to have good ways to detect and prevent them. Recognizing cyber threats quickly …

[HTML][HTML] Android Malware Detection and Identification Frameworks by Leveraging the Machine and Deep Learning Techniques: A Comprehensive Review

SK Smmarwar, GP Gupta, S Kumar - Telematics and Informatics Reports, 2024 - Elsevier
The ever-increasing growth of online services and smart connectivity of devices have posed
the threat of malware to computer system, android-based smart phones, Internet of Things …

Automated android malware detection using optimal ensemble learning approach for cybersecurity

H Alamro, W Mtouaa, S Aljameel, AS Salama… - IEEE …, 2023 - ieeexplore.ieee.org
Current technological advancement in computer systems has transformed the lives of
humans from real to virtual environments. Malware is unnecessary software that is often …

[HTML][HTML] AI-powered malware detection with Differential Privacy for zero trust security in Internet of Things networks

F Nawshin, D Unal, M Hammoudeh, PN Suganthan - Ad Hoc Networks, 2024 - Elsevier
The widespread usage of Android-powered devices in the Internet of Things (IoT) makes
them susceptible to evolving cybersecurity threats. Most healthcare devices in IoT networks …

Detecting android malware using deep learning algorithms: A survey

A Alzubaidi - Computers and Electrical Engineering, 2024 - Elsevier
Malware designers and developers persistently endeavor to target smartphone users with
the aim of collecting personal information, infringing on their privacy, and jeopardizing their …

Quantum‐Neural Network Model for Platform Independent Ddos Attack Classification in Cyber Security

MY Küçükkara, F Atban… - Advanced Quantum …, 2024 - Wiley Online Library
Abstract Quantum Machine Learning (QML) leverages the transformative power of quantum
computing to explore a broad range of applications, including optimization, data analysis …

[PDF][PDF] Explainable Classification Model for Android Malware Analysis Using API and Permission-Based Features.

N Aslam, IU Khan, SA Bader, A Alansari… - … , Materials & Continua, 2023 - researchgate.net
One of the most widely used smartphone operating systems, Android, is vulnerable to cutting-
edge malware that employs sophisticated logic. Such malware attacks could lead to the …

Detection of android malware using machine learning and siamese shot learning technique for security

FA Almarshad, M Zakariah, GA Gashgari… - IEEE …, 2023 - ieeexplore.ieee.org
Android malware security tools that can swiftly identify and categorize various malware
classes to create rapid response strategies have been trendy in recent years. Although …

Deep learning-based improved transformer model on android malware detection and classification in internet of vehicles

N Almakayeel - Scientific Reports, 2024 - nature.com
With the growing popularity of autonomous vehicles (AVs), confirming their safety has
become a significant concern. Vehicle manufacturers have combined the Android operating …

Intelligent Pattern Recognition using Equilibrium Optimizer with Deep Learning Model for Android Malware Detection

M Maray, M Maashi, HM Alshahrani, SS Aljameel… - IEEE …, 2024 - ieeexplore.ieee.org
Android malware recognition is the procedure of mitigating and identifying malicious
software (malware) planned to target Android operating systems (OS) that are extremely …