Whale Optimization Algorithm for Feature Selection Enhances Classification in Malware Datasets

Abstract

Malicious programs are increasing abnormally, affecting our everyday lives. Modern sophisticated and agile malware programs are not always detected by traditional malware detection methods that use signature-based techniques. As a result, researchers use behavior-based techniques to analyze malware behaviors (features). However, malware features derived from behavioral analysis commonly suffer from high dimensionality. Accordingly, this work applies the Whale Optimization Algorithm (WOA) to find the optimal subset of features in the CIC-MalMem-2022 dataset. Feature selection contributes significantly to reducing high-dimensionality issues and improving malware detection performance. WOA is employed to enhance the efficiency of the selection process for the optimal features and determine the most advantageous set of features by omitting redundant and irrelevant features. In addition, we apply the K-nearest neighbor algorithm (KNN) to detect malware. Using WOA and KNN, this study improves the detection efficiency of CIC-MalMem-2022. According to the findings, the proposed method outperforms existing malware detection systems, including detection fitness value, accuracy, consuming time, and the number of selected features. Received: 2 September 2024 | Revised: 11 November 2024 | Accepted: 21 November 2024 Conflicts of Interest The authors declare that they have no conflicts of interest in this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Mariam Al Ghamri: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing, Supervision, Project administration. Dyala Ibrahim: Conceptualization, Validation, Formal analysis, Writing – original draft, Writing – review & editing, Project administration. Rami Sihwail: Methodology, Validation, Data curation, Writing – original draft, Writing – review & editing. Mohammad Shehab: Methodology, Software, Validation, Investigation, Data curation, Writing – original draft, Writing – review & editing, Visualization.