Journal of Cybersecurity and Information Management JCIM 2690-6775 2769-7851 10.54216/JCIM https://www.americaspg.com/journals/show/3399 2019 2019 Department of Computer Sciences, College of Computer and Information Technology, University of Anbar, Anbar, Iraq Khattab Khattab Department of Computer Networking Systems, College of Computer and Information Technology, University of Anbar, Anbar, Iraq Khattab M. Ali Alheeti The continual increase of cyber dangers necessitates creative techniques to better the identification and mitigation of malware. This research provides a cutting-edge examination of employing the Random Forest Classifier in combination with electromagnetic side-channel analysis for finding malicious software. Electromagnetic side-channel analysis harnesses the accidental information leakage from electronic systems, giving it a formidable tool for studying the underlying workings of gadgets. This study reveals how these electromagnetic side-channel signals may be used to identify subtle and evasive malware activities. The paper goes into the theoretical basis of electromagnetic side-channel analysis and the actual application of the Random Forest Classifier in this setting. By analyzing electromagnetic emissions, a wide range of devices and systems can be scrutinized for the telltale signs of malware-induced behaviors. Experimental results illustrate the effectiveness of this approach, showcasing the model demonstrated high accuracy, with an accuracy rate of up to 97%, demonstrating its ability to effectively leverage electromagnetic side-channel information for malicious program detection for enhanced cybersecurity measures. 2025 2025 233 243 10.54216/JCIM.150218 https://www.americaspg.com/articleinfo/2/show/3399