A Feasibility Study on Evasion Attacks Against NLP-Based Macro Malware Detection Algorithms

A Feasibility Study on Evasion Attacks Against NLP-Based Macro Malware Detection Algorithms

Machine learning-based models for malware detection have gained prominence in order to detect obfuscated malware. These models extract malicious features and endeavor to classify samples as either malware or benign entities. Conversely, these benign features can be employed to imitate benign samples...

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Bibliographic Details
Main Authors: Mamoru Mimura, Risa Yamamoto
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Macro malware
machine learning
evasion attack
LSA
paragraph vector
Online Access:https://ieeexplore.ieee.org/document/10345584/

Internet

https://ieeexplore.ieee.org/document/10345584/

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