A STUDY ON DIGITAL FORENSICS USING VARIOUS ALGORITHMS FOR MALWARE DETECTION

Dr. Anjana Pandey, Shruti Mujmer, Poorvi Gyar, Sarthak Kanungo

Abstract


Malware Detection is a field of Digital Forensics which involves detection of known and unknown malware by various methods. Detection of real-time malware becomes a big challenge, the research done in the field has shown the advancement achieved in malware detection system designs and implementations. Although each malware is unique, malware has some common behavioral characteristics which can be examined and used for malware detection. This paper has a survey and analysis of various research works on Malware Detection using behavior characteristics and also introduces its problems and issues. Finally, we have compared various machine learning algorithms which can be used for most effective malware detection process. The implementation and the results of the study show that the Random Forest algorithm is a most efficient algorithm for detection of malicious files in any system.

 


Keywords


malware; malware detection; machine learning; algorithm; malicious files; dataset

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References


Liu Wu, Ren Ping, Lui Kie, Wu Jian Ping, Liu Ke.”Analysis and Forensics for Behavior Characteristics of Malware on the Internet”, 2016 IEEE International conference on digital signal processing, 2016.

Wu, Ke Liu, Ping Ren, Donghong Sun, Jian Ping Wu, Ke Liu. "Analysis and forensics for Behavior Characteristics of Malware on Internet", 2016 14th Annual Conference on Privacy, Security and Trust (PST), 2016

. Priyank Singhal, Natasha Raul, 2012. Malware Detection Module using Machine Learning Algorithms to Assist in Centralized Security in Enterprise Networks in International Journal of Network Security & Its Applications (IJNSA), Vol.4, No.1, January 2012

Muhammad Salman Khan, Sana Siddiqui, Robert D. McLeod, Ken Ferens, Witold Kinsner."Fractal-based adaptive boosting algorithm for cognitive detection of computer malware", 2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), 2016.

. Mohammad Akour, Izzat Alsmadi, Mamoun Alazab: The Malware Detection Challenge of Accuracy, Student Paper submitted to University of Balamand.

Da-Yu Kao, Guan-Jie Wu:”A Digital Triage Forensics Framework of Window malware forensic toolkit: Based on ISO/IEC 27037:2012", 2015 International Carnahan Conference on Security Technology (ICCST), 2015

. Sudhir Kumar Pandey, B.M.Mehtre: Performance of Malware Detection Tools: A Comparison 2014 IEEE International Conference on Advanced Communications Control and Computing Technologies, 2014

Kwong Sak Leung. "Data Mining on DNA Sequences of Hepatitis B Virus", IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2009

Anaconda download and installation https://www.anaconda.com/download/ documentation https://www.anaconda.com/what-is-anaconda/ and https://enterprise-docs.anaconda.com/en/latest/ ,and cheat sheets https://conda.io/docs/_downloads/conda-cheatsheet.pdf

Jupyter notebook download and installation

https://www.anaconda.com/download/

. Anaconda information

https://en.wikipedia.org/wiki/Anaconda_(Python_distribution)

C.C.C. Pang, A.R.M. Upton, G. Shine, M.V. Kamath. "A comparison of algorithms for detection of spikes in the electroencephalogram", IEEE Transactions on Biomedical Engineering, 2003




DOI: https://doi.org/10.26483/ijarcs.v9i3.6084

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