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All Journal Intechno Journal : Information Technology Journal Applied Information Technology and Computer Science (AICOMS)
Ghufron Zaida Muflih
Universitas Ma'arif Nahdlatul Ulama Kebumen
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Analisis Host-Based Digital Forensics terhadap Artefak Penggunaan Tor browser pada Sistem Operasi Linux Rico Saputra; Ghufron Zaida Muflih
Applied Information Technology and Computer Science (AICOMS) Vol 5 No 1 (2026): AICOMS
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/e4aq5a03

Abstract

The use of Tor Browser as a digital anonymity platform continues to increase alongside the growing demand for internet privacy. Although Tor is designed to conceal user identities and activities through onion routing mechanisms, previous studies have shown that digital artifacts can still be recovered from the host system. This study aims to analyze the existence of digital artifacts generated by Tor Browser usage on the BackBox Linux operating system using a host-based digital forensics approach. The research employed an experimental method consisting of seven testing scenarios, namely behavioral forensic leakage, session persistence, cross-session correlation, host versus virtualization comparison, memory footprint analysis, network pattern consistency, and passive onion observation. Data acquisition and analysis were conducted using Autopsy, Hindsight, Plaso, LiME, Volatility, Bulk Extractor, and Wireshark. The results indicate that Tor Browser usage still leaves digital artifacts within storage media, volatile memory, and network traffic. This study concludes that the host-based digital forensics approach remains effective for identifying Tor Browser activities in Linux environments.
Deepfake Content Analysis Using Error Level Analysis and Metadata Kurnia Nur Hikmah; Ghufron Zaida Muflih
Intechno Journal : Information Technology Journal Vol. 8 No. 1 (2026): July
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/intechnojournal.2026v8i1.2904

Abstract

Purpose: The spread of deepfakes on platform X threatens the integrity of digital information, but previous research has applied Metadata Analysis, Error Level Analysis (ELA), and Reality Defender separately, not yet as an integrated approach. This study applied Metadata Analysis and ELA to identify manipulation in deepfake images, as well as evaluate the effectiveness of Reality Defender in detecting deepfake content in images circulating on platform X as an application case study. Methods/Study design/approach: Using a descriptive qualitative approach with digital forensic experiment methods, seven purposive selected image samples representing seven content characteristic scenarios (original, face-swap, GAN, full generative AI, anti-forensics, conventionally edited, and platform compressed), analyzed through three layered stages with tiered final classification criteria based on the cross-validated Reality Defender score threshold with ELA. Result/Findings: Metadata is only informative before uploading, as X deletes EXIF uniformly post-upload. ELA remained effective in both conditions, showing localized intensity anomalies (close to 240-255 from 255) across deepfake samples. Reality Defender correctly classified six of the seven samples (85.7% accuracy, 100% in the deepfake category, 66.7% in the original category), with one false positive (64%) in the original, conventionally edited image. Novelty/Originality/Value: This study integrated all three methods simultaneously and layered with explicit criteria, showing Metadata lost post-upload diagnostic value while ELA and Reality Defender remained the most reliable for content sourced from platform X.
Co-Authors Kurnia Nur Hikmah Rico Saputra