00abf1e8-6190-4890-9817-2503d874a34f beie director@blueeyesintelligence.org 10.35940/ijrte.F5545.039621 AV-TEST (2019), The Independent IT-Security Institute, https://www.av-test.org/en/statistics/malware/. Accessed 2 November 2019.Kaspersky Security Bulletin (2016), Overall statistics, https://securelist.com/kaspersky-security-bulletin-2016-e xecutive-summary/76858/. Accessed 12 May 2016.McAfee Labs Threats Report (2017),https://www.mcafee.com/us/resources/reports/rp-quarterl y-threats-jun-2017.pdf. Accessed 2 June 2017.10.1016/j.compeleceng.2013.11.024Chandrashekar G. and Sahin F., "A survey on feature selection methods", Computers & Electrical Engineering., vol. 40(1), 2014, pp.16-28.10.35940/ijeat.B4666.129219HarshaLatha P. and Mohanasundaram R, "A New Hybrid Strategy for Malware Detection Classification with Multiple Feature Selection Methods and Ensemble Learning Methods", International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249-8958., vol. 9(2), 2019, pp. 4013-4019.10.1186/s13635-019-0098-ySharma J, Charul G, Ole-Christoffer G., and G. Morten G., "Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation", EURASIP Journal on Information Security., vol. 15(1), 2019. pp. 15-27.10.1109/ACCESS.2020.2986014Euh S., Hyunjong L, Donghoon K., and Doosung H., "Comparative Analysis of Low-Dimensional Features and Tree-Based Ensembles for Malware Detection Systems", IEEE Access., vol. 8(2), 2020 pp. 76796-76808.10.1109/MALWARE.2010.5665796Tian R., Islam L, Batten L, and Versteeg S., "Differentiating malware from cleanware using behavioural analysis", 5th international conference on malicious and unwanted software, IEEE, 2010.10.1007/s11416-015-0261-zDamodaran A., Troia F.D., Visaggio A., Austin H, .Stamp A., Comparison of static, dynamic, and hybrid analysis for malware detection, Journal of Computer Virology and HackingTechniques., vol. 13(1), 2017, pp.1-12.10.1007/978-3-319-59870-3_10Fang Y., Yu B., Tang Y., Liu L., Lu Z., Wang Y, and Yang Q. "A new malware classification approach based on malware dynamic analysis", In Australasian onference on Information Security and Privacy, Springer, Cham, 2017, pp. 173-189.10.1109/TrustCom.2016.0163Zhang Y., Huang Q., Ma X, Yang Z, and Jiang J. "Using multi-features and ensemble learning method for imbalanced malware classification", IEEE Trustcom/BigDataSE/ISPA, IEEE, 2016, pp. 965-973.10.1155/2014/260905Bai, J. Wang, and G. Zou G., "A malware detection scheme based on mining format information, Sci. World Journal, vol. 12(4), 2014 pp. 36-48.Ninite (2019). Benign data, www.ninite.com. Accessed in 29 November 2019.Download (2018). Benign data, www.downloads.com. Accessed in 29 November 2019.Softpedia (2019). Benign data, www.softpedia.com. Accessed in 29 November 2019.Totalvirus (2019). Online file checker, www.totalvirus.com. Accessed in 29 November 2019.Virushare (2019). Malware data, www.virushare.com. Accessed in 22 November 2019.Virussign (2019). Malware data, www.virussign.com. Accessed in 22 November 2019.10.1109/MALWARE.2011.6112319Singh A, and Lakhotia A., "Game-theoretic design of an information exchange model for detecting packed malware in Malicious and Unwanted Software" (MALWARE), 6th International Conference, 2011, pp. 1-7 .10.1145/3136625Li J., Cheng K., Wang S., Morstatter F., Trevino R.P., Tang J., and Liu H., "Feature selection: A data perspective", ACM Computing Surveys (CSUR)., vol. 50(6), 2018, pp. 94-100,Schultz M.G., Eskin E, Zadok F., and Stolfo S.J., "Data mining methods for detection of new malicious executables" Proc. IEEE Symp. Security, Privacy, 2001.Konstantinou E. and Wolthusen S. Metamorphic Virus. Analysis and Detection, Technical Report RHUL-MA-2008-02, Royal Holloway University of London, 2008.10.1016/S1532-0464(03)00034-0Dreiseitl S.and Ohno-Machado L., "Logistic regression and artificial neural network classification models: a methodology review, Journal of Biomedical Informatics, vol. 35(6), 2002, pp. 352-359.10.1007/BF00058655Breiman L., "Bagging predictors", Machine Learning, vol. 24, 2002, pp. 123-140.Ke G., Meng Q., Finley T., Wang T., Chen W., Ma W, Q. Ye Q., and .Liu T.Y., " LightGBM: A Highly Efficient Gradient Boosting Decision Tree", 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA, 2017.Ramnathv and Gdequeiroz (2017), "Gradient Boosting Machines", https://github.com/ledell/useR-machinelearning-tutorial/blob/master/gradient-boosting-machines. Accessed 25 Sepember (2017).Dada E.G., Bassi J.S., Hurcha Y.J. and Alkali A.H. , "Performance Evaluation of Machine Learning Algorithms for Detection and Prevention of Malware Attacks", IOSR Journal of Computer Engineering (IOSR-JCE)., vol. 21(3),2019, pp. 18-27.10.35940/ijitee.B8009.129219HarshaLatha P. and Mohanasundaram R. "Improving Malware Detection Classification Accuracy with Feature Selection Methods and Ensemble-based Machine Learning Methods", International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3071, vol. 9(2), 2019, pp. 2055-2059.