Predicting Fraud Apps using Hybrid Learning Approach

International Journal of Computer Science and Engineering

© 2018 by SSRG - IJCSE Journal

Volume 5 Issue 6

Year of Publication : 2018

Authors : K.Aishwarya, C.Selvi

10.14445/23488387/IJCSE-V5I6P103

How to Cite?

K.Aishwarya, C.Selvi, "Predicting Fraud Apps using Hybrid Learning Approach," SSRG International Journal of Computer Science and Engineering , vol. 5,  no. 6, pp. 1-5, 2018. Crossref, https://doi.org/10.14445/23488387/IJCSE-V5I6P103

Abstract:

Mobile phone has become the target for risky and snoopy applications. The android’s current risk communication technique depends on users to identify the permissions that an app is requesting. But the users are unaware of permissions as it requires some technical knowledge. Therefore, android’s protection against malicious application is risk communication method where any user who wishes to install an app will be warned about permissions, the application would call for and then the user has to take the proper decision. In Google play, the users frequently download and use several applications from various unknown vendors. Therefore, the protection against malware applications should depend on decisions made by users. The main part of protection against malware on mobile devices is to alert the users about malware and permit them to take decisions about whether to choose and install specific apps. Compute risk score that users can apply while choosing applications whether they want to use that app or not.

Keywords:

Android Devices, Security Fraud detection, Reviews.

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