SAMADroid: A Novel 3-Level Hybrid Malware Detection Model for Android Operating System
作者： Saba Arshad , Munam A. Shah , Abdul Wahid , Amjad Mehmood , Houbing Song
DOI: 10.1109/ACCESS.2018.2792941
关键词: Android (operating system) 、 Feature extraction 、 Static analysis 、 Embedded system 、 Computer science 、 Malware analysis 、 Android malware 、 Malware 、 Mobile device 、 Upload
摘要: … In this paper, a novel 3-level hybrid Android malware detection model is proposed named as SAMADroid. It is a hybrid between three levels for malware analysis and detection: i) Static …
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Nello Cristianini, John Shawe-Taylor, An Introduction to Support Vector Machines and Other Kernel-based Learning Methods ,(2000)
Building and Applying Logistic Regression Models John Wiley & Sons, Inc.. pp. 137- 172 ,(2003) , 10.1002/9780470114759.CH5
Hsin-Yu Chuang, Sheng-De Wang, Machine Learning Based Hybrid Behavior Models for Android Malware Analysis 2015 IEEE International Conference on Software Quality, Reliability and Security. pp. 201- 206 ,(2015) , 10.1109/QRS.2015.37
Per-Erik Danielsson, Euclidean distance mapping Computer Graphics and Image Processing. ,vol. 14, pp. 227- 248 ,(1980) , 10.1016/0146-664X(80)90054-4
Ugur Pehlivan, Nuray Baltaci, Cengiz Acarturk, Nazife Baykal, The analysis of feature selection methods and classification algorithms in permission based Android malware detection 2014 IEEE Symposium on Computational Intelligence in Cyber Security (CICS). pp. 1- 8 ,(2014) , 10.1109/CICYBS.2014.7013371
Thomas Bläsing, Leonid Batyuk, Aubrey-Derrick Schmidt, Seyit Ahmet Camtepe, Sahin Albayrak, An Android Application Sandbox system for suspicious software detection international conference on malicious and unwanted software. pp. 55- 62 ,(2010) , 10.1109/MALWARE.2010.5665792
Kabakus Abdullah Talha, Dogru Ibrahim Alper, Cetin Aydin, APK Auditor: Permission-based Android malware detection system Digital Investigation. ,vol. 13, pp. 1- 14 ,(2015) , 10.1016/J.DIIN.2015.01.001
P.V. Shijo, A. Salim, Integrated Static and Dynamic Analysis for Malware Detection Procedia Computer Science. ,vol. 46, pp. 804- 811 ,(2015) , 10.1016/J.PROCS.2015.02.149
Wen-Chieh Wu, Shih-Hao Hung, DroidDolphin: a dynamic Android malware detection framework using big data and machine learning research in adaptive and convergent systems. pp. 247- 252 ,(2014) , 10.1145/2663761.2664223
D. Dittman, T. M. Khoshgoftaar, R. Wald, A. Napolitano, Random forest: A reliable tool for patient response prediction bioinformatics and biomedicine. pp. 289- 296 ,(2011) , 10.1109/BIBMW.2011.6112389