Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hirofumi Nakakoji"'
Autor:
Tomohiro Shigemoto, Yasuhiro Fujii, Hiroaki Kikuchi, Shota Fujii, Hirofumi Nakakoji, Ichiro Kuriama, Tetsuro Kito
Publikováno v:
AsiaJCIS
In order to minimize the damage caused by Remote Access Tool (RAT) malware used in targeted attacks, various countermeasures such as the black list and white list approaches have been developed. In the black list approach, we manage servers where the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b22aebd1c02e206bcc9d866ae57b19b2
https://doi.org/10.1109/asiajcis.2018.00024
https://doi.org/10.1109/asiajcis.2018.00024
Autor:
Naoki Shimotsuma, Hirofumi Nakakoji, Hiroaki Kikuchi, Tetsuro Kito, Nobutaka Kawaguchi, Yoshiaki Isobe, Tomohiro Shigemoto, Yasuhiro Fujii, Naoki Hayashi
Publikováno v:
NBiS
In recent years, the damage from cyber attacks caused by sophisticated malware has continuously increased. It is therefore becoming more difficult to take countermeasures using traditional approaches such as antivirus and firewall products. Against t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dbc4f2c974741e718aea0abe0071fc70
https://doi.org/10.1109/nbis.2016.25
https://doi.org/10.1109/nbis.2016.25
Autor:
Hirofumi Nakakoji, Tetsuro Kito, Kazuya Okochi, Nobutaka Kawaguchi, Tomohiro Shigemoto, Masato Terada
Publikováno v:
2010 6th IEEE Workshop on Secure Network Protocols.
As P2P (Peer-to-Peer) file sharing software is widely deployed, it causes some serious problems, such as network traffic congestion, unwanted file sharing by computer viruses that abuse P2P software, and so on. Detecting and controlling traffic of P2
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7828526ce583b80f18f25e8728f4880
https://doi.org/10.1109/npsec.2010.5634449
https://doi.org/10.1109/npsec.2010.5634449
Autor:
Tetsuro Kito, Nobutaka Kawagcuhi, Kazuya Okouchi, Tomonori Shigemoto, Hirofumi Nakakoji, Masato Terada
Publikováno v:
SAINT
In this paper, we propose a bot detection method that enhances traffic analysis of Network based IDS (NIDS) by using process contextual information obtained from monitored machines. Existing NIDS classifies hosts suspected of doing both of the Comman
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3dbc79332b5e80ca8419f4e9c11be80d
https://doi.org/10.1109/saint.2010.106
https://doi.org/10.1109/saint.2010.106