Citation
Abdul Rahman, Siti Husna and Manalan, Kirtanah and Mohd Fathil, Nur Haifa and Zainuddin, Ahmad Anwar (2025) From Detection to Evidence: A Unified System for Automated Email Phishing Analysis and Forensic Logging. In: 9th International Conference on Information Technology, InCIT 2025, 12 November 2025 - 14 November 2025, Hybrid, Phuket.|
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Abstract
Phishing attacks continue to bypass traditional defenses and burden non-technical users with manual, errorprone investigations. Existing tools are largely detectioncentric and rarely preserve evidence in a structured, reusable form, leaving a gap between threat identification and postincident analysis. We present a unified web-based system that automates email ingestion, multi-engine scanning, and forensic logging within a single interface. Implemented as a full-stack Python (Flask) application with MongoDB, the system programmatically acquires emails (or user-uploaded .eml), submits artifacts to VirusTotal, and parses headers to extract and geolocate sender IPs, maintaining user-scoped, audit-ready records. A dashboard provides real-time status, verdict visualization, and access to detailed reports and header forensics. In evaluation with 20 emails (10 phishing, 10 benign), the system achieved 95% accuracy (≥ 90% target), while soak testing demonstrated stable operation over extended runtime. By coupling automated detection with structured, user-specific forensic records, the system reduces technical barriers and strengthens incident response, making email threat analysis more accessible to both non-technical users and security teams.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | Phishing detection, email forensics |
| Subjects: | Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science |
| Divisions: | Faculty of Computing and Informatics (FCI) |
| Depositing User: | Ms Rosnani Abd Wahab |
| Date Deposited: | 18 Mar 2026 08:07 |
| Last Modified: | 19 Mar 2026 01:20 |
| URII: | http://shdl.mmu.edu.my/id/eprint/15576 |
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