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IRSHAD, A. MAUYA, R. DUTTA, M. BURGET, R. UHER, V.
Originální název
Feature Optimization for Run Time Analysis of Malware in Windows Operating System using Machine Learning Approach
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
With the development of the web's high usage, the number of malware affecting the system are incresing. Various techniques have been used but they are incapable to identify unknown malware. To counter such threats, the proposed work makes utilization of dynamic malware investigation systems based on machine learning technique for windows based malware recognization. In this paper two methods to analyses the behaviour of the malware and feature selection of windows executables file. Cuckoo is a malicious code analysis apparatus which analyzes the malware more detail and gives the far-reaching results dependent on the arrangement of tests made by it and second, the feature selection for windows dynamic malware anaysis has been done by using Genetic Algorithm. Three classifiers have been used to compare the detection result of Windows-based malware: Support Vector Machine with detection accuracy of 81.3%, Naive Bayes classifier with accuracy of 64.7% and Random Forest classifier achieving 86.8% accurate results.
Klíčová slova
Malware;Feature extraction;Genetic algorithms;Microsoft Windows;Tools;Machine learning algorithms;Machine learning
Autoři
IRSHAD, A.; MAUYA, R.; DUTTA, M.; BURGET, R.; UHER, V.
Vydáno
1. 7. 2019
Nakladatel
IEEE
Místo
Budapest, Hungary
ISBN
978-1-7281-1864-2
Kniha
2019 42nd International Conference on Telecommunications and Signal Processing (TSP)
Strany od
255
Strany do
260
Strany počet
6
URL
https://ieeexplore.ieee.org/document/8768808
BibTex
@inproceedings{BUT159837, author="Areeba {Irshad} and Ritesh {Mauya} and Malay Kishore {Dutta} and Radim {Burget} and Václav {Uher}", title="Feature Optimization for Run Time Analysis of Malware in Windows Operating System using Machine Learning Approach", booktitle="2019 42nd International Conference on Telecommunications and Signal Processing (TSP)", year="2019", pages="255--260", publisher="IEEE", address="Budapest, Hungary", doi="10.1109/TSP.2019.8768808", isbn="978-1-7281-1864-2", url="https://ieeexplore.ieee.org/document/8768808" }