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Conference Paper
Cloud-Based Android Botnet Malware Detection System
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- Authors
- Suyash Jadhav, Shobhit Dutia, Kedarnath Calangutkar, Tae Oh, Young Ho Kim, Joeng Nyeo Kim
- Issue Date
- 2015-07
- Citation
- International Conference on Advanced Communication Technology (ICACT) 2015, pp.347-352
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Increased use of Android devices and its open source development framework has attracted many digital crime groups to use Android devices as one of the key attack surfaces. Due to the extensive connectivity and multiple sources of network connections, Android devices are most suitable to botnet based malware attacks. The research focuses on developing a cloud-based Android botnet malware detection system. A prototype of the proposed system is deployed which provides a runtime Android malware analysis. The paper explains architectural implementation of the developed system using a botnet detection learning dataset and multi-layered algorithm used to predict botnet family of a particular application.
- KSP Keywords
- Android Devices, Android Malware, Android botnet, Attack Surface, Botnet detection, Detection Systems(IDS), Development framework, Layered algorithm, Malware detection, Multiple sources, Network connection