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It is a fact that more and more users are adopting the online digital payment systems via mobile devices for everyday use. This attracts powerful gangs of cybercriminals, which use sophisticated and highly intelligent types of malware to broaden their attacks. Malicious software is designed to run quietly and to remain unsolved for a long time. It manages to take full control of the device and to communicate (via the Tor network) with its Command u0026 Control servers of fast-flux botnets’ networks to which it belongs. This is done to achieve the malicious objectives of the botmasters. This paper proposes the development of the computational intelligence anti-malware framework (CIantiMF) which is innovative, ultra-fast and has low requirements. It runs under the android operating system (OS) and its reasoning is based on advanced computational intelligence approaches. The selection of the android OS was based on its popularity and on the number of critical applications available for it. The CIantiMF uses two advanced technology extensions for the ART java virtual machine which is the default in the recent versions of android. The first is the smart anti-malware extension, which can recognize whether the java classes of an android application are benign or malicious using an optimized multi-layer perceptron. The optimization is done by the employment of the biogeography-based optimizer algorithm. The second is the Tor online traffic identification extension, which is capable of achieving malware localization, Tor traffic identification and botnets prohibition, with the use of the online sequential extreme learning machine algorithm.

Computational intelligence anti-malware framework for android OS