Article Per Year (5 Year)
p-Index From 2021 - 2026
3.703
P-Index
This Author published in this journals
All Journal Jurnal Pseudocode Jurnal Computech & Bisnis (e-Journal) Jurnal Teknik Informatika (JUTIF) Acman: Accounting and Management Journal Informatics Management, Engineering and Information System Journal Electronic, Business, Management and Technology Journal Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Majalah Bisnis & IPTEK Journal of Economics, Management, and Entrepreneurship Jurnal Pengabdian Masyarakat: Bisnis dan Iptek (JPMBISTEK)
Asep Ririh Riswaya
STMIK Mardira Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Social Sciences Other

Published : 31 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 31 Documents
Search

 1   2   3   4 
Forensic Evaluation of the Effectiveness of Private Browsing Modes in Google Chrome and Mozilla Firefox Using the National Institute of Standards and Technology Framework Integrated with Artificial Intelligence Syukri, Muhammad; Riswaya, Asep Ririh; Budiman, Dheni Apriantsani
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5577

Abstract

As cyber threats and the misuse of personal data continue to increase, private browsing modes in web browsers such as Google Chrome and Mozilla Firefox are often perceived as solutions to enhance user privacy. However, these modes still leave traces of sensitive data in volatile memory (RAM), even though artifacts stored on disk-based storage are removed. This study evaluates the effectiveness of private browsing modes using the National Institute of Standards and Technology (NIST) framework integrated with Artificial Intelligence (AI) for forensic analysis. Simulation scenarios were conducted to assess the ability of private browsing modes to prevent data retention. The results indicate that although private browsing modes successfully eliminate disk-based traces, sensitive data such as account credentials can still be extracted from RAM. The integration of AI accelerates the detection of these artifacts. This research contributes to the field of digital forensics by providing a systematic framework for evaluating browser privacy mechanisms and offering insights for the development of real-time browser security tools.
Co-Authors . Komarudin Abdul Fadlil Abdurahman Fauzi Achyar Nuraulia Rahman Ade Supriatna Aep Syaripudin Agni Ahmad Saripudin Agung Wahana Agung Wahana Agung Wahana Alfi Yudin Raihan Anisa, Tasya Nurul Anjas Tryana Anton Yudhana Aris Koharudin Farras Asep Maulana Ashwin Sasongko Budiman, Dheni Apriantsani Dadi Rosadi Damayanti, Elok Dimas Nurdiansyah Eka P. Sakti Fadhlan Hadyan Nadhir Fika Amalia, Fika Fikri Irawan Abdurahman Hadian Hadian Hadian Hadian Hasan Abdurahman Hasyifa Nur Fadhillah Heri Wahyudi Jajat sudrajat Kiki Agustin Marjito Marjito Maulana, Aris Ilham Muhammad Naufal Muhammad Syukri Nengsih, Nengsih Noerrohmah, Syifa Oji Tiongkos Maruli Chrismas Oktavia Oktavia Oktavia Oktavia Retnowaty, Agung Tri Ricky Rohmanto Rizky Panji Santoni Rizky Panji Santoni Rizqiati, Fitri Sandri Arya Fikriawan Septian Adiraharja Sigit Aprilian Sirozudin Ibnu Farhan Solihin Solihin Suprianto Suprianto Suwandana Suryana Putera Tay, En Yusup Saepulloh