2024
DOI: 10.1186/s42400-024-00205-z
|View full text |Cite
|
Sign up to set email alerts
|

Enhanced detection of obfuscated malware in memory dumps: a machine learning approach for advanced cybersecurity

Md. Alamgir Hossain,
Md. Saiful Islam

Abstract: In the realm of cybersecurity, the detection and analysis of obfuscated malware remain a critical challenge, especially in the context of memory dumps. This research paper presents a novel machine learning-based framework designed to enhance the detection and analytical capabilities against such elusive threats for binary and multi type’s malware. Our approach leverages a comprehensive dataset comprising benign and malicious memory dumps, encompassing a wide array of obfuscated malware types including Spyware,… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2025
2025

Publication Types

Select...
3
1
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
references
References 35 publications
0
0
0
Order By: Relevance