Presentation 2020-11-26
Function Estimation for Malwares based on Similarity and Its Effectiveness
Kohei Kodama, Hiroshi Kai, Masakatu Morii,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, we consider about a method which estimates malware functions using the results of malware dynamic analysis. We obtain the malware similarity by N-gram or longest common subsequence (LCS) and evaluate the function points of the known malwere. We show the effectiveness of the method through computer experiments using the function points and the discriminant analysis method.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Malware / Function estimation / Dynamic Analysis Logs
Paper # ICSS2020-21
Date of Issue 2020-11-19 (ICSS)

Conference Information
Committee ICSS
Conference Date 2020/11/26(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Security, etc.
Chair Hiroki Takakura(NII)
Vice Chair Katsunari Yoshioka(Yokohama National Univ.) / Kazunori Kamiya(NTT)
Secretary Katsunari Yoshioka(NICT) / Kazunori Kamiya(KDDI labs.)
Assistant Keisuke Kito(Mitsubishi Electric) / Toshihiro Yamauchi(Okayama Univ.)

Paper Information
Registration To Technical Committee on Information and Communication System Security
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Function Estimation for Malwares based on Similarity and Its Effectiveness
Sub Title (in English)
Keyword(1) Malware
Keyword(2) Function estimation
Keyword(3) Dynamic Analysis Logs
1st Author's Name Kohei Kodama
1st Author's Affiliation Ehime University(Ehime Univ.)
2nd Author's Name Hiroshi Kai
2nd Author's Affiliation Ehime University(Ehime Univ.)
3rd Author's Name Masakatu Morii
3rd Author's Affiliation Kobe University(Kobe Univ.)
Date 2020-11-26
Paper # ICSS2020-21
Volume (vol) vol.120
Number (no) ICSS-264
Page pp.pp.13-16(ICSS),
#Pages 4
Date of Issue 2020-11-19 (ICSS)