Z. Bazrafshan, H. Hashemi, S. M. Fard, and A. Hamzeh, A survey on heuristic malware detection techniques, The 5th Conference on Information and Knowledge Technology, pp.113-120, 2013.
DOI : 10.1109/IKT.2013.6620049

Y. Ye, T. Li, Q. Jiang, and Y. Wang, CIMDS: Adapting postprocessing techniques of associative classification for malware detection, IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, vol.40, pp.298-307, 2010.

I. June, Anti-malware vendors slow to respond. Computer Fraud & Security, pp.1-2, 2010.

Z. Salehi, A. Sami, and M. Ghiasi, Using feature generation from API calls for malware detection, Computer Fraud & Security, vol.2014, issue.9, pp.9-18, 2014.
DOI : 10.1016/S1361-3723(14)70531-7

J. D. Aycock, Computer viruses and malware, 2006.

A. Shabtai, R. Moskovitch, Y. Elovici, and C. Glezer, Detection of malicious code by applying machine learning classifiers on static features: A state-of-the-art survey, Information Security Technical Report, vol.14, issue.1, pp.16-29, 2009.
DOI : 10.1016/j.istr.2009.03.003

P. Fornasini, The Chi Square test. The Uncertainty in Physical Measurements:An Introduction to Data Analysis in the Physics Laboratory, pp.187-198, 2009.

J. J. Rodríguez, L. I. Kuncheva, and C. J. Alonso, Rotation Forest: A New Classifier Ensemble Method, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.28, issue.10, pp.1619-1630, 2006.
DOI : 10.1109/TPAMI.2006.211

I. H. Witten and E. Frank, Data mining, ACM SIGMOD Record, vol.31, issue.1, 2005.
DOI : 10.1145/507338.507355

M. Pietrek, Peering Inside the PE: A Tour of the Win32 Portable Executable File Format, Microsoft Systems Journal-US Edition, vol.9, pp.15-38, 1994.

M. G. Schultz, E. Eskin, E. Zadok, and S. J. Stolfo, Data mining methods for detection of new malicious executables, Proceedings 2001 IEEE Symposium on Security and Privacy. S&P 2001, pp.38-49, 2001.
DOI : 10.1109/SECPRI.2001.924286

C. Wang, J. Pang, R. Zhao, and X. Liu, Using API Sequence and Bayes Algorithm to Detect Suspicious Behavior, 2009 International Conference on Communication Software and Networks, pp.544-548, 2009.
DOI : 10.1109/ICCSN.2009.60

S. Available-at-koskska and C. Nevison, Statistical tables and formulae. Springer text in statistics, 1989.

D. P. Farrington and R. Loeber, Relative improvement over chance (RIOC) and phi as measures of predictive efficiency and strength of association in 2???2 tables, Journal of Quantitative Criminology, vol.8, issue.3, pp.201-213, 1989.
DOI : 10.2466/pr0.1986.58.2.615