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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] |
2022-02-22 11:55 |
Online |
Online |
Bit-plane oriented Detection method of Malicious Code Hidden in the Image Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) ITS2021-50 IE2021-59 |
With the increasing importance of cyberspace, the threat of malware has also been increasing. Malware which hides malici... [more] |
ITS2021-50 IE2021-59 pp.151-156 |
IA |
2021-10-15 16:50 |
Online |
Online |
Malware Traffic Detection at Certain Time Using IP Flow Information Seiya Komatsu, Yusei Katsura, Masatoshi Kakiuchi, Ismail Arai, Kazutoshi Fujikawa (NAIST) IA2021-27 |
The damage caused by the activities of malware such as botnets and ransomware has become a social problem. In order to d... [more] |
IA2021-27 pp.6-11 |
ISEC, IT, WBS |
2020-03-11 11:20 |
Hyogo |
University of Hyogo (Cancelled but technical report was issued) |
Applying Machine Learning to Malware Detection in Mobile Applications Yoshiki Kusama, Keiji Takeda, Kazuma Kobayashi, Osamu Nakamura (Keio Univ.), Lee Myoungje (LINE corp.) IT2019-112 ISEC2019-108 WBS2019-61 |
In this paper, we proposed and implemented a detection method that focuses on a binary file stored in an APK(Android app... [more] |
IT2019-112 ISEC2019-108 WBS2019-61 pp.151-157 |
ICSS |
2019-11-13 14:20 |
Miyazaki |
MRT Terrace(Miyazaki) |
Issue on Adversarial Malware Sample Generation using Reinforcement Learning against Machine Learning Based Malware Detection System Seiya Takagi, Hirokazu Hasegawa, Yukiko Yamaguchi, Hajime Shimada (Nagoya Univ.) ICSS2019-62 |
In recent years, security researchers have applied machine learning techniques to malware detection researches to improv... [more] |
ICSS2019-62 pp.13-18 |
ISEC, SITE, LOIS |
2019-11-02 15:00 |
Osaka |
Osaka Univ. |
On Robustness of Machine-Learning-Based Malware Detection Wanjia Zheng (U. Tsukuba), Kazumasa Omote (U. Tsukuba/NICT) ISEC2019-83 SITE2019-77 LOIS2019-42 |
As the 2020 Tokyo Olympics are approaching, the possibility of being targeted by attackers has further increased in Japa... [more] |
ISEC2019-83 SITE2019-77 LOIS2019-42 pp.133-140 |
ISEC, SITE, ICSS, EMM, HWS, BioX, IPSJ-CSEC, IPSJ-SPT [detail] |
2019-07-24 10:55 |
Kochi |
Kochi University of Technology |
Investigation on Blockchain-based Malware Information Sharing Method in Malware Detection System Ryusei Fuji, Shotaro Usuzaki, Kentaro Aburada, Hisaaki Yamaba, Tetsuro Katayama (Univ. of Miyazaki), Mirang Park (Kanagawa Inst. of Tech.), Norio Shiratori (Chuo Univ.), Naonobu Okazaki (Univ. of Miyazaki) ISEC2019-45 SITE2019-39 BioX2019-37 HWS2019-40 ICSS2019-43 EMM2019-48 |
Rapid malware detection is very important because malware causes serious damage to the modern society based on the Inter... [more] |
ISEC2019-45 SITE2019-39 BioX2019-37 HWS2019-40 ICSS2019-43 EMM2019-48 pp.293-298 |
ICSS |
2017-11-20 15:15 |
Oita |
Beppu International Convention Center |
Preliminary Evaluation on the Program Classification at the Processor Level using Machine Learning Ryotaro Kobayashi (Kogakuin Univ.), Hayate Takase, Genki Otani, Ren Ohmura (Toyohashi Univ. of Tech.), Masahiko Kato (Univ. of Nagasaki) ICSS2017-39 |
As use of IoT devices becomes widespread, a lot of things are connected to the Internet, and the convenience of everyday... [more] |
ICSS2017-39 pp.5-10 |
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