Mohammad Ababneh*, Ayat Al-Droos, Ammar El-Hassan
Computer Systems Science and Engineering, Vol.48, No.5, pp. 1171-1191, 2024, DOI:10.32604/csse.2024.052875
Abstract With the high level of proliferation of connected mobile devices, the risk of intrusion becomes higher. Artificial Intelligence (AI) and Machine Learning (ML) algorithms started to feature in protection software and showed effective results. These algorithms are nonetheless hindered by the lack of rich datasets and compounded by the appearance of new categories of malware such that the race between attackers’ malware, especially with the assistance of Artificial Intelligence tools and protection solutions makes these systems and frameworks lose effectiveness quickly. In this article, we present a framework for mobile malware detection based on a… More >
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