Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Mojtaba Haderbadi"'
Early Detection of the Advanced Persistent Threat Attack Using Performance Analysis of Deep Learning
Autor:
Javad Hassannataj Joloudari, Mojtaba Haderbadi, Amir Mashmool, Mohammad Ghasemigol, Shahab S. Band, Amir Mosavi
Publikováno v:
IEEE Access, Vol 8, Pp 186125-186137 (2020)
One of the most common and critical destructive attacks on the victim system is the advanced persistent threat (APT)-attack. An APT attacker can achieve its hostile goal through obtaining information and gaining financial benefits from the infrastruc
Externí odkaz:
https://doaj.org/article/8ba546e7e48041c3a97b875a207bde6e
Early detection of the advanced persistent threat attack using performance analysis of deep learning
Autor:
Mohammad GhasemiGol, Shahab S. Band, Mojtaba Haderbadi, Amir Mashmool, Amir Mosavi, Javad Hassannataj Joloudari
Publikováno v:
IEEE Access, Vol 8, Pp 186125-186137 (2020)
IEEE Access
IEEE Access
One of the most common and important destructive attacks on the victim system is Advanced Persistent Threat (APT)-attack. The APT attacker can achieve his hostile goals by obtaining information and gaining financial benefits regarding the infrastruct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b05da324ed2ad85eec7a5f6034cb979c
http://arxiv.org/abs/2009.10524
http://arxiv.org/abs/2009.10524
Autor:
Amir Mashmool, Mohammad GhasemiGol, Javad Hassannataj Joloudari, Amir Mosavi, Mojtaba Haderbadi, Shahaboddin Shamshirband
One of the most common and important destructive attacks on the victim system is Advanced Persistent Threats (APT)-attack. The APT attacker can achieve his hostile goals by obtaining information and gaining financial benefits regarding the infrastruc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2afe502a52fdfdad886ac9bb688f13c1
https://doi.org/10.20944/preprints202007.0745.v1
https://doi.org/10.20944/preprints202007.0745.v1