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학술대회 Cloud-Based Android Botnet Malware Detection System
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저자
Suyash Jadhav, Shobhit Dutia, Kedarnath Calangutkar, Tae Oh, 김영호, 김정녀
발행일
201507
출처
International Conference on Advanced Communication Technology (ICACT) 2015, pp.347-352
DOI
https://dx.doi.org/10.1109/ICACT.2015.7224817
협약과제
15MS3600, 모바일 단말의 비인가 접근 차단 및 안전한 운영환경 보장을 위한 EAL 4급 군사용 융합 보안 솔루션 개발, 김정녀
초록
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 제안 키워드
Android Devices, Android Malware, Android botnet, Attack Surface, Botnet detection, Cloud-based, Development framework, Intrusion detection system(IDS), Layered algorithm, Malware detection, Multiple sources