Evaluations of AI‐based malicious PowerShell detection with feature optimizations

Evaluations of AI‐based malicious PowerShell detection with feature optimizations

Cyberattacks are often difficult to identify with traditional signature‐based detection, because attackers continually find ways to bypass the detection methods. Therefore, researchers have introduced artificial intelligence (AI) technology for cybersecurity analysis to detect malicious PowerShell s...

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Bibliographic Details
Main Authors: Jihyeon Song, Jungtae Kim, Sunoh Choi, Jonghyun Kim, Ikkyun Kim
Format: Article
Language:English
Published: Electronics and Telecommunications Research Institute (ETRI) 2021-04-01
Series:ETRI Journal
Subjects:
deep learning
feature optimization
fileless malware
machine learning
powershell script
Online Access:https://doi.org/10.4218/etrij.2020-0215

Internet

https://doi.org/10.4218/etrij.2020-0215

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