An adaptive neuro-fuzzy inference system for multinomial malware classification

An adaptive neuro-fuzzy inference system for multinomial malware classification

Malware detection and classification are important requirements for information security because malware poses a great threat to computer users. As the growth of technology increases, malware is getting more sophisticated and thereby more difficult to detect. Machine learning techniques have been e...

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Bibliographic Details
Main Authors: Amos Orenyi Bajeh, Mary Olayinka Olaoye, Fatima Enehezei Usman-Hamza, Ikeola Suhurat Olatinwo, Peter ogirima Sadiku, Abdulkadir Bolakale Sakariyah
Format: Article
Language:English
Published: Nigerian Society of Physical Sciences 2025-02-01
Series:Journal of Nigerian Society of Physical Sciences
Subjects:
Malware
Adaptive neuro-fuzzy inference system
Artificial intelligence
Fuzzy logic
Artificial neural network
Online Access:https://journal.nsps.org.ng/index.php/jnsps/article/view/2172
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