Results 1 to 10 of about 3,123 (222)

Metaheuristics with Deep Learning Model for Cybersecurity and Android Malware Detection and Classification [PDF]

Applied Sciences, 2023
Since the development of information systems during the last decade, cybersecurity has become a critical concern for many groups, organizations, and institutions.
Ashwag Albakri, Fatimah Alhayan, Nazik Alturki, Saahirabanu Ahamed, Shermin Shamsudheen   +4 more
doaj   +2 more sources

A Review of Android Malware Detection Approaches Based on Machine Learning

IEEE Access, 2020
Android applications are developing rapidly across the mobile ecosystem, but Android malware is also emerging in an endless stream. Many researchers have studied the problem of Android malware detection and have put forward theories and methods from ...
Kaijun Liu, Guoai Xu
exaly   +3 more sources

DroidDetectMW: A Hybrid Intelligent Model for Android Malware Detection

Applied Sciences, 2023
Malicious apps specifically aimed at the Android platform have increased in tandem with the proliferation of mobile devices. Malware is now so carefully written that it is difficult to detect.
Fatma Taher, Omar AlFandi, Mousa Al-kfairy, Hussam Al Hamadi, Saed Alrabaee   +4 more
doaj   +3 more sources

Android malware detection with MH-100K: An innovative dataset for advanced research. [PDF]

Data Brief, 2023
Bragança H, Rocha V, Barcellos L, Souto E, Kreutz D, Feitosa E.   +5 more
europepmc   +2 more sources

GSIDroid: A Suspicious Subgraph-Driven and Interpretable Android Malware Detection System. [PDF]

Sensors (Basel)
Huang H, Huang W, Jiang F.
europepmc   +3 more sources

Android malware detection using hybrid ANFIS architecture with low computational cost convolutional layers. [PDF]

PeerJ Comput Sci, 2022
Atacak İ, Kılıç K, Doğru İA.
europepmc   +2 more sources

The rise of obfuscated Android malware and impacts on detection methods [PDF]

PeerJ Computer Science, 2022
The various application markets are facing an exponential growth of Android malware. Every day, thousands of new Android malware applications emerge. Android malware hackers adopt reverse engineering and repackage benign applications with their malicious
Wael F. Elsersy, Ali Feizollah, Nor Badrul Anuar   +2 more
doaj   +2 more sources

Obfuscated Malware Detection and Classification in Network Traffic Leveraging Hybrid Large Language Models and Synthetic Data [PDF]

Sensors
Android malware detection remains a critical issue for mobile security. Cybercriminals target Android since it is the most popular smartphone operating system (OS). Malware detection, analysis, and classification have become diverse research areas.
Mehwish Naseer, Farhan Ullah, Samia Ijaz, Hamad Naeem, Amjad Alsirhani, Ghadah Naif Alwakid, Abdullah Alomari   +6 more
doaj   +2 more sources

Android Malware Category and Family Identification Using Parallel Machine Learning [PDF]

Journal of Information Technology Management, 2022
Android malware is one of the most dangerous threats on the Internet.  It has been on the rise for several years.  As a result, it has impacted many applications such as healthcare, banking, transportation, government, e-commerce, etc.
Ahmed Hashem El Fiky, Mohamed Ashraf Madkour, Ayman El Shenawy   +2 more
doaj   +1 more source

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

Sci Rep
Almakayeel N.
europepmc   +3 more sources