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안드로이드 악성 앱 탐지율 향상을 위한 특성 분석 및 기계학습 모델에 관한 연구  

Kang, Hoyoung (고려대학교 정보보호대학원)
Son, Geunsoo (한화시스템)
Son, Minwoo (한양대학교 소프트웨어학부)
Song, Yuseok (성균관대학교 반도체시스템공학과)
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Chun-Hao Yung and Wen-Shenq Juang, "Static and Dynamic Integrated Analysis Scheme for Android Malware", Journal of Electronic Science an Technology, Vol.15, No.3, pp.246-250. 2017.
2 Jae-wook Jang, Jaesung Yun, Aziz Mohaisen, Jiyoung Woo, and Huy Kang Kim, "Detecting and classifying method based on similarity matching of Android malware behavior with profile," SpringerPlus, 5:273, December 2016.   DOI
3 Jae-wook Jang, Jaesung Yun, Jiyoung Woo, and Huy Kang Kim, "Andro-profiler: anti-malware system based on behavior profiling of mobile malware," Proceedings of the 23rd International Conference on World Wide Web, pp. 737-738, April 2014.
4 김동욱 외, "안드로이드 플랫폼에서 악성 행위 분석을 통한 특징 추출과 머신러닝 기반 악성 어플리케이션 분류", 한국인터넷정보학회, 제19권 제1호, pp.27-35, 2018.
5 Pengbin Feng. et al, "A Novel Dynamic Android Malware Detection System with Ensemble Learning", IEEE Access, Vol.6, pp.30996-31011, 2018.   DOI
6 Sebastian Raschka and Vahid Mirjalili, Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition, Packt Publishing, September 2017.
7 A.M. Aswini, P.Vinod, "Android Malware Analysis Using Ensemble Features", Security, Privacy, and Applied Cryptography Engineering: 4th International Conference, SPACE 2014, Pune, India, October 18-22, 2014.