Refining malware analysis with enhanced machine learning algorithms using hyperparameter tuning
Many researchers address challenges and limitations inherent to machine learning algorithms to optimize classifier performance. Overfitting, a prevalent issue, arises when models are excessively complex and trained on noisy data, leading to suboptimal generalization to new data. Another concern is u...
Main Authors: | El Mouhtadi, Walid, El Bakkali, Mohamed, Maleh, Yassine, Mounir, Soufyane, Ouazzane, Karim |
---|---|
Format: | Article |
Language: | English |
Published: |
InderScience
2024
|
Subjects: | |
Online Access: | https://repository.londonmet.ac.uk/8932/1/2023_IJCCBS-170512%20%285%29.pdf |
Similar Items
-
Cybersecurity-based blockchain for cyber-physical systems: challenges and applications
by: Maleh, Yassine, et al.
Published: (2023) -
Machine learning techniques for Secure Edge SDN
by: Maleh, Yassine, et al.
Published: (2024) -
A comprehensive taxonomy of social engineering attacks and defense mechanisms: toward effective mitigation strategies
by: Zaoui, Mohamed, et al.
Published: (2024) -
A maturity capability framework for security operation center
by: Taqafi, Issam, et al.
Published: (2022) -
A new framework of feature engineering for machine learning in financial fraud detection
by: Ikeda, Chie, et al.
Published: (2020)