Statistical Analysis for Classification of Malicious Software

This paper proposes a new method of the malicious code classification based on statistical analysis of traces WinAPI calls. We have developed a procedure for programs proximity measurement, taking into account the sequence of WinAPI calls, and the similarity of their arguments. Cluster analysis is u...

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Main Authors:	Evgeny Petrovich Tumoyan, Ksenia Vasilevna Tsyganok
Format:	Article
Language:	English
Published:	Moscow Engineering Physics Institute 2014-09-01
Series:	Bezopasnostʹ Informacionnyh Tehnologij
Subjects:	multidimensional scaling WinAPI calls viruses
Online Access:	https://bit.mephi.ru/index.php/bit/article/view/180

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spelling	doaj-5fdd707c2bfb433696f15b2e127b5f7a2020-11-24T21:29:50ZengMoscow Engineering Physics Institute Bezopasnostʹ Informacionnyh Tehnologij2074-71282074-71362014-09-01213180Statistical Analysis for Classification of Malicious SoftwareEvgeny Petrovich Tumoyan0Ksenia Vasilevna Tsyganok1Southern Federal UniversitySouthern Federal UniversityThis paper proposes a new method of the malicious code classification based on statistical analysis of traces WinAPI calls. We have developed a procedure for programs proximity measurement, taking into account the sequence of WinAPI calls, and the similarity of their arguments. Cluster analysis is used to identify groups programs and classification of the programs.https://bit.mephi.ru/index.php/bit/article/view/180multidimensional scalingWinAPI callsviruses
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Evgeny Petrovich Tumoyan Ksenia Vasilevna Tsyganok
spellingShingle	Evgeny Petrovich Tumoyan Ksenia Vasilevna Tsyganok Statistical Analysis for Classification of Malicious Software Bezopasnostʹ Informacionnyh Tehnologij multidimensional scaling WinAPI calls viruses
author_facet	Evgeny Petrovich Tumoyan Ksenia Vasilevna Tsyganok
author_sort	Evgeny Petrovich Tumoyan
title	Statistical Analysis for Classification of Malicious Software
title_short	Statistical Analysis for Classification of Malicious Software
title_full	Statistical Analysis for Classification of Malicious Software
title_fullStr	Statistical Analysis for Classification of Malicious Software
title_full_unstemmed	Statistical Analysis for Classification of Malicious Software
title_sort	statistical analysis for classification of malicious software
publisher	Moscow Engineering Physics Institute
series	Bezopasnostʹ Informacionnyh Tehnologij
issn	2074-7128 2074-7136
publishDate	2014-09-01
description	This paper proposes a new method of the malicious code classification based on statistical analysis of traces WinAPI calls. We have developed a procedure for programs proximity measurement, taking into account the sequence of WinAPI calls, and the similarity of their arguments. Cluster analysis is used to identify groups programs and classification of the programs.
topic	multidimensional scaling WinAPI calls viruses
url	https://bit.mephi.ru/index.php/bit/article/view/180
work_keys_str_mv	AT evgenypetrovichtumoyan statisticalanalysisforclassificationofmalicioussoftware AT kseniavasilevnatsyganok statisticalanalysisforclassificationofmalicioussoftware
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Statistical Analysis for Classification of Malicious Software

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