Hybrid Browser-Based Framework for Mobile Threat Detection and Forensic Analysis

Muttath Francis, Roshan (2025) Hybrid Browser-Based Framework for Mobile Threat Detection and Forensic Analysis. Masters thesis, Dublin, National College of Ireland.

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Abstract

Mobile forensic investigations require secure, portable, and intelligent tools to address evolving threats. This research offers a Hybrid Threat Detection Framework that combines various methods of detection in order to provide full forensic reach. The architecture includes YARA-based signature scanning for accurate recognition of well-known malware families, regex-based Indicator of Compromise (IoC) extraction for quick identification of suspicious patterns like URLs, IP addresses, and email identifiers, and an RNN-driven WhatsApp chat toxicity analysis module for the detection of abusive or harmful communications. The system facilitates the analysis of a wide variety of digital artifacts, such as APKs, SQLite databases, log files, and chat exports, in their entirety offline via WebAssembly and JavaScript to maintain privacy protection, platform neutrality, and cross-device compatibility. ALEAPP parsing also adds to the capabilities of the framework by reconstructing timelines for devices, interpreting app history usage, and detecting removed or suspicious system events. All detection results are aggregated into formatted, legally defensible reports in PDF, CSV, and JSON formats, facilitating easy integration into investigative processes. Performance testing shows that the RNN toxicity classification component attains 91% accuracy with minimal latency for real-time processing. By integrating technical malware detection with behavioral threat analysis, the presented framework arms investigators with a field-capable, privacy-friendly of tools that boosts the efficacy and consistency of modern mobile forensic investigations.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Prior, Michael UNSPECIFIED
Uncontrolled Keywords:	Mobile forensics; YARA rules; regex detection; ALEAPP; progressive web app
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > QA Mathematics > Computer software > Mobile Phone Applications T Technology > T Technology (General) > Information Technology > Computer software > Mobile Phone Applications
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	16 Jun 2026 13:38
Last Modified:	16 Jun 2026 13:38
URI:	https://norma.ncirl.ie/id/eprint/9362

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