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Latest issue : Volume 10 Issue 1 Articles In press. A plagiarism check will be implemented for all the articles using world-renowned software.
Digital Object Identifier will be assigned for all the articles being published in the Journal from September issue, i. Volume 3, Issue 9, DOI Prefix : ISSN Online K Thejeswari, Dr. K Sreenivasulu, Ms. Pullaiah College of Engineering and Technology , Kurnool Abstract : Malicious attacks on Android mobile devices have increased as smartphone usage has grown rapidly. The Android systems accommodate a variety of important approaches, like banking applications; hence, they become the target of malware that uses security system vulnerabilities.
The cyber threat has grown exponentially over the past decade. Cybercriminals have become highly experienced. Current security regulators were insufficient to protect networks from an increasing number of highly skilled cybercriminals. The latest advances in Artificial Intelligence AI methods have led to a high level of innovation and automation. While the AI techniques provide important advantages, they could be utilized maliciously.
The latest creation of cyber threats leverages modern AI artificial intelligence -aided techniques that are efficient for launching multi-level, potent, and potentially devastating attacks. Present cyber defence systems face different problems in protecting against recent and emerging risks. Hence, in this work, a cyber-threat security system using artificial intelligence for Android-operated mobile devices is presented. The machine learning ML and deep learning DL algorithms can conveniently identify threats on Android mobile devices.