Zero-day Android botnet detection using neural networks

• Published in: Neural computing & applications Vol. 37; no. 17; pp. 10795 - 10805
• Main Authors: Seraj, Saeed, Pimenidis, Elias, Trovati, Marcello, Polatidis, Nikolaos
• Format: Journal Article
• Language: English
• Published: London Springer London 01.06.2025; Springer Nature B.V
• Subjects: Artificial Intelligence; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Malware; Multilayer perceptrons; Neural networks; Probability and Statistics in Computer Science; Remote control; S.I.: Timely Advances of Deep Learning with applications and Data Driven Modeling; Special Issue on Timely Advances of Deep Learning with applications and Data Driven Modeling; New dataset; Android malware detection; Neural networks; Botnets
• ISSN: 0941-0643; 1433-3058; 1433-3058
• DOI: 10.1007/s00521-024-10818-7

Android devices have evolved to offer a diverse array of services, spanning applications related to banking, business, health, and entertainment. The widespread adoption of Android devices, coupled with the open-source architecture of the Android operating system, has rendered them a prime target for malicious actors. Among the most perilous threats are Android botnets, which enable malicious actors, often referred to as botmasters, to exert remote control for the execution of destructive attacks. Android botnets have huge potential to be an emerging threat to mobile device security. In this paper, we focus on detecting evolving Android botnets and introduce a new dataset of 3458 apps, represented by 455 permission-based features. We propose an improved multilayer perceptron neural network for zero-day botnet detection. Our methodology, in this way, achieves an accuracy of 98.5%, thus outperforming traditional classifiers. It has a lot of functionality and is based on the neural network approach, making it able to identify slight botnet behaviours in order to improve Android security.