THE METHODS OF ARTIFICIAL INTELLIGENCE FOR MALICIOUS APPLICATIONS DETECTION IN ANDROID OS - Bezobrazov, Sergei; Sachenko, Anatoly; Komar, Myroslav; Rubanau, Vladimir (International Journal of Computing, 2016)
This paper presents and discusses a method for Android’s applications classification with the purpose of malware detection. Based on the application of an Artificial Immune System and Artificial Neural Networks we propose the “antivirus” system especially for Android system that can detect and block undesirable and malicious applications. This system can be characterized by self-adaption and self-evolution and can detect even unknown and previously unseen malicious applications. The proposed system is the part of our team’s big project named “Intelligent Cyber Defense System” that includes malware detection and classification module, intrusions detection and classification module, cloud security module and personal cryptography module. This paper contains the extended research that was presented during the IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS’2015) [1].