id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ejpam-6542	Ahmad, Sadique ; A.Elaffendi, Mohammed; Ahmad, Naveed; Shah, Ismail	Machine Learning-Enhanced Simulation of Multi-Vector Email Malware Spread in Organizational Networks	2025	24	.pdf	application/pdf	6752	387	54	By replacing traditional signature-based detection with our adap- tive approach, security teams can achieve substantial improvements in threat detection while reducing false positives, our validation studies demonstrated a 28% reduction in false alerts while maintaining high detection rates. The system (1) extends classical epidemiological frameworks with three key innovations specific to organizational email threats: Exposed State (E) captures the incubation period I. Shah et al. / Eur.	cache/ejpam-6542.pdf	txt/ejpam-6542.txt