Analysis of features selection and machine learning classifier in android malware detection

ICISA 2014 - 2014 5th International Conference on Information Science and Applications

Volumn , Issue , 2014, Pages

  Mas'Ud, Mohd Zaki ^a   Sahib, Shahrin ^a   Abdollah, Mohd Faizal ^a   Selamat, Siti Rahayu ^a   Yusof, Robiah ^a  

^a UNIVERSITI TEKNIKAL MALAYSIA MELAKA   (Malaysia)

Author keywords

Android; Android malware detection; Feature Selection; Machine Learning; Mobile malware

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER CRIME; FEATURE EXTRACTION; INFORMATION SCIENCE; LEARNING SYSTEMS; MALWARE; MOBILE DEVICES; SOCIAL NETWORKING (ONLINE);

ANDROID; ANDROID APPLICATIONS; ANDROID MALWARE; FALSE POSITIVE RATES; LEARNING CLASSIFIERS; MOBILE APPLICATIONS; MOBILE MALWARE; TRUE POSITIVE RATES;

ANDROID (OPERATING SYSTEM);

EID: 84904490791     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICISA.2014.6847364     Document Type: Conference Paper

References (17)

1. InternationalTelecommunicationsUnion (ITU) , The World in 2013: ICT Facts and Figures. Updated December 2013. [Online] Retrieved on December 2013 from http://www.itu.int/en/ITUD/ Statistics/Pages/stat/default.aspx.
2. Christian Funk and Maria Garnaeva, "Kaspersky Security Bulletin 2013. Overall statistics for 2013", (Securelist), [online] Retrieved on December 2013 http://www.securelist.com/en/analysis/204792318/Kaspersky- Security- Bulletin-2013-Overall-statistics-for-2013
3. La Polla, M.; Martinelli, F.; Sgandurra, D., "A Survey on Security for Mobile Devices," Communications Surveys & Tutorials, IEEE , vol.15, no.1, pp.446,471, First Quarter 2013 doi: 10.1109/SURV.2012.013012.00028
4. Shabtai, Asaf, Uri Kanonov, Yuval Elovici, Chanan Glezer, and Yael Weiss. ""Andromaly": a behavioral malware detection framework for android devices."Journal of Intelligent Information Systems 38, no. 1 (2012): 161-190.
5. Distler, Dennis, "Malware Analysis: An Introduction", SANS Institute InfoSec Reading Room. [online] Retrieve on July 2013 from https://www.sans.org/reading-room/whitepapers/malicious/malwareanalysis- introduction-2103
6. Android System Call, Retrieved on January 2014 [online]https://github. com/android/platform-bionic/blob/master/libc/SY SCALLS.TXT
7. Burguera, Iker, Urko Zurutuza, and Simin Nadjm-Tehrani. "Crowdroid: behavior-based malware detection system for android." In Proceedings of the 1st ACM workshop on Security and privacy in smartphones and mobile devices, pp. 15-26. ACM, 2011.
8. Isohara, T.; Takemori, K.; Kubota, A., "Kernel-based Behavior Analysis for Android Malware Detection," Computational Intelligence and Security (CIS), 2011 Seventh International Conference on , vol., no., pp.1011,1015, 3-4 Dec. 2011 doi: 10.1109/CIS.2011.226
9. Abela, Kevin Joshua, Jan Raynier Delas Alas, Don Kristopher Angeles, Robert Joseph Tolentino, and Miguel Alberto Gomez. "Automated Malware Detection for Android AMDA." In The Second International Conference on Cyber Security, Cyber Peacefare and Digital Forensic (CyberSec2013), pp. 180-188. The Society of Digital Information and Wireless Communication, 2013.
10. Dini, Gianluca, Fabio Martinelli, Andrea Saracino, and Daniele Sgandurra. "MADAM: a multi-level anomaly detector for android malware." In Computer Network Security, pp. 240-253. Springer Berlin Heidelberg, 2012.
11. Zhou, Yajin, and Xuxian Jiang. "Dissecting android malware: Characterization and evolution." In Security and Privacy (SP), 2012 IEEE Symposium on, pp. 95-109. IEEE, 2012
12. Imam, I. F., Michalski,R. S.,&Kerschberg, L. "Discovering attribute dependence in databases by integrating symbolic learning and statistical analysis techniques". In Proceeding of the AAAI- 93 workshop on knowledge discovery in databases, 1993
13. Shannon, C. E, "The mathematical theory of communication", The Bell system Technical Journal, 27(3), 379-423, 1948.
14. Feizollah, Ali, Nor Badrul Anuar, Rosli Salleh, Fairuz Amalina, Ra'uf Ridzuan Ma'arof, and Shahaboddin Shamshirband. "A Study Of Machine Learning Classifiers for Anomaly-Based Mobile Botnet Detection." Malaysian Journal of Computer Science 26, no. 4 , 2014.
15. Garner, S.R., "Weka: The Waikato Environment for Knowledge Analysis." In Proceedings of the 1995 New Zealand Computer Science Research Students Conference, 57-64, 1995.
16. B. Sanz, I. Santos, X. Ugarte-Pedrero, C. Laorden, J. Nieves, y P.G. Bringas Instance-based Anomaly Method for Android Malware Detection. En Proceedings of the 10th International Conference on Security and Cryptography (SECRYPT). Reykjavik (Iceland), 29-31 July 2013, pp. 387-394, ISBN: 978-989-8565-73-0
17. Firdausi, Ivan, Charles Lim, Alva Erwin, and Anto Satriyo Nugroho. "Analysis of machine learning techniques used in behavior-based malware detection." In Advances in Computing, Control and Telecommunication Technologies (ACT), 2010 Second International Conference on, pp. 201-203. IEEE, 2010.