It is a fact that more and more users are adopting\nthe online digital payment systems via mobile devices for\neveryday use. This attracts powerful gangs of cybercriminals,\nwhich use sophisticated and highly intelligent types of malware\nto broaden their attacks. Malicious software is designed\nto run quietly and to remain unsolved for a long time. It manages\nto take full control of the device and to communicate (via\nthe Tor network) with its Command&Control; servers of fastflux\nbotnets� networks to which it belongs. This is done to\nachieve the malicious objectives of the botmasters. This paper\nproposes the development of the computational intelligence\nanti-malware framework (CIantiMF) which is innovative,\nultra-fast and has low requirements. It runs under the android\noperating system (OS) and its reasoning is based on advanced\ncomputational intelligence approaches. The selection of the\nandroid OS was based on its popularity and on the number\nof critical applications available for it. The CIantiMF uses\ntwo advanced technology extensions for the ART java virtual\nmachine which is the default in the recent versions of android.\nThe first is the smart anti-malware extension, which can recognize\nwhether the java classes of an android application\nare benign or malicious using an optimized multi-layer perceptron.\nThe optimization is done by the employment of the\nbiogeography-based optimizer algorithm. The second is the\nTor online traffic identification extension, which is capable\nof achieving malware localization, Tor traffic identification and botnets prohibition, with the use of the online sequential\nextreme learning machine algorithm.
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