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Detecting malicious Android applications based on the network packets generated
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DOI：10.1016/j.neucom.2020.08.095.png)
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Abstract
En 中文
Widespread communication by mobile devices today has promoted the use of huge amounts of information on them. Malware applications are undergoing exponential growth, directly attacking these smart phones to steal information. For this reason, we have created a methodology to analyze the network packets sent by any type of mobile applications in order to validate their behavior. In order to solve this problem, we have used supervised learning systems in an attempt to modelize the traffic communication with a set of previously labeled data. This will help to actively detect if applications installed in mobile devices could be tagged as malicious. (c) 2021 Elsevier B.V. All rights reserved.
Keywords:
Malware detection
Machine learning
Network traffic analysis
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