Publication: A new system call classification of mobile malwares for SMS exploitation
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Date
2017
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Publisher
American Scientific Publishers
Abstract
Android mobile devices are used for various applications. Online banking and shopping are increasingly being performed on smartphones. As the role of smartphones in business grows, the floodgates have opened mobile devices to malware threats, which can be exploited for malicious purposes. Mobile malware is growing in sophistication and continues to target consumers. Consumers are charged without affirmative consent. As a solution to this challenge, we proposed a system call classification based on surveillance exploitation system calls for SMS. The proposed system calls classification is evaluated and tested using applications from Google Play Store. This research focuses on Android operating system. The experiment was conducted using Drebin dataset which contains 5560 malware applications. Dynamic analysis was used to extract the system calls from each application in a controlled lab environment. This research has developed a new mobile malware classification for Android smartphone using a covering algorithm. The classification has been evaluated in 500 applications and 126 applications have been identified to contain malware. � 2017 American Scientific Publishers All rights reserved.
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Keywords
Android, Big data, Covering algorithm, Data classification, Mobile malware