Presentation 2019-07-04
Android Malware Detection Scheme Based on Level of SSL Server Certificate
Hiroya Kato, Shuichiro Haruta, Iwao Sasase,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, in order to detect Android malwares which encrypt packets, we propose an Android malware detection scheme based on level of SSL server certificate. Attackers tend to use an untrusted certificate to encrypt malicious payloads in many cases because passing rigorous examination is required to get a trusted certificate. Thus, we utilize SSL server certificate based features for detection since their certificates tend to be untrusted. Furthermore, in order to obtain the more exact features, we introduce required permission based weight values because malwares inevitably require permissions regarding malicious actions. By computer simulation with real dataset, we show our scheme achieves an accuracy of 92.7 %. Our scheme can cope with encrypted malicious payloads and 89 malwares which are not detected by the previous scheme.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Android malwares / SSL / Machine Learning
Paper # CS2019-15
Date of Issue 2019-06-27 (CS)

Conference Information
Committee CS
Conference Date 2019/7/4(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Amami City Social Welfare Center
Topics (in Japanese) (See Japanese page)
Topics (in English) Next Generation Networks, Access Networks, Broadband Access, Power Line Communications, Wireless Communication Systems, Coding Systems, etc.
Chair Hidenori Nakazato(Waseda Univ.)
Vice Chair Jun Terada(NTT)
Secretary Jun Terada(Waseda Univ.)
Assistant Kazutaka Hara(NTT) / Hiroyuki Saito(OKI)

Paper Information
Registration To Technical Committee on Communication Systems
Language ENG-JTITLE
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Android Malware Detection Scheme Based on Level of SSL Server Certificate
Sub Title (in English)
Keyword(1) Android malwares
Keyword(2) SSL
Keyword(3) Machine Learning
1st Author's Name Hiroya Kato
1st Author's Affiliation Keio University(Keio Univ.)
2nd Author's Name Shuichiro Haruta
2nd Author's Affiliation Keio University(Keio Univ.)
3rd Author's Name Iwao Sasase
3rd Author's Affiliation Keio University(Keio Univ.)
Date 2019-07-04
Paper # CS2019-15
Volume (vol) vol.119
Number (no) CS-101
Page pp.pp.13-18(CS),
#Pages 6
Date of Issue 2019-06-27 (CS)