Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Intelligent Systems and Information Technology
Faizal, Arif
Unknown Affiliation
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Design of Forensic Analysis Framework for Single-Page Web Applications Faizal, Arif
Journal of Intelligent Systems and Information Technology Vol. 2 No. 2 (2025): July
Publisher : Apik Cahaya Ilmu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61971/jisit.v2i2.163

Abstract

The Single-Page Application (SPA) architecture based on React, Vue, or Angular has revolutionized browser development with a dynamic user experience. However, its complexity poses challenges for forensic analysis that have not yet been maximally addressed by conventional frameworks. This research designs an open-source forensic testing framework specifically for SPAs, integrating volatile memory acquisition, client-side artifact analysis, and log correlation on APIs. This hybrid method combines live memory forensics with API transaction tracing to reconstruct user activity longitudinally. Evaluation of 15 SPAs showed that the framework successfully identified 92% of XSS and injection traces missed by traditional forensic tools, with a 40% improvement in user session reconstruction. The novelty of the research lies in the SPA-specific modules for virtual DOM extraction and state management, temporal integration using Plaso for synchronizing client-side events and server-side logs, and the adaptation of open-source forensic tools for the SPA environment. In this study, blind spots in forensic activities such as the dynamism of client-side rendering and encrypted API calls can be addressed. Case studies illustrate the effectiveness in uncovering credential hijacking in Vue.js applications. This framework provides a foundation with standards for SPA investigations that critically combine aspects of cloud, client, and API forensics.
Co-Authors