Integrated Cyber Forensic for E-Mail Analysis Framework

Abstract

Objectives: This study presents a distinct technique for classifying emails based on data processing and mining, trimming , refinement, and then adapts several algorithms to classify these emails. Methods/Statistical Analysis: SWARM algorithm to obtain practical and accurate results. Findings: The proposed system is capable of learning in an environment with large and variable data. To test the proposed system, we have to select available data which Enron Data set. A high accuracy rate (95%) was obtained, which is higher than the classification rates mentioned in previous research papers presented in section 2 in this paper. Application/ Improvements: In the past two decades, the Internet has become as an open, publicly and widely used as a source of data transmission and exchanging the messages between criminals,