Belkasoft Evidence Center X

Belkasoft Evidence Center X is a digital forensics and cyber incident response (DFIR) software developed by Belkasoft.^[1][2][3] It is used by law enforcement agencies, corporate security teams, and forensic analysts to acquire, analyze, and report on digital evidence from a variety of sources, including computers, mobile devices, memory dumps, cloud services, and emerging data types like drones and car systems.^[4][3]

Belkasoft Evidence Center X

Developer(s)	Belkasoft
Operating system	Windows
Type	Digital forensics, Incident response
License	Proprietary
Website	belkasoft.com/x

The software supports data extraction from physical and logical drives, mobile device backups, and forensic images. It includes tools for parsing artifacts, analyzing media, examining live RAM, and reconstructing timelines.^[5][6]

Features

Belkasoft Evidence Center X offers several features:^[7][8][9]

• Mobile acquisition: Supports iOS data access using checkm8 and agent-based methods, and Android extraction through ADB, agent-based, and chipset-specific methods.
• Cloud analysis: Support for iCloud, Google Cloud, WhatsApp, Instagram, Microsoft 365, and Google Workspace.
• Encryption handling: Includes decryption of APFS, BitLocker, TrueCrypt, and others.
• Forensic analysis: 1,500+ artifact types; SQLite and system file examination.
• Visualization tools: Provides tools for creating timelines and connection graphs for data correlation.
• AI integration: BelkaGPT, an offline forensic assistant for plain-language search and semantic insights.

Further reading

• Purwanto, S. B., & Zamroni, G. M. (2019). Digital Forensic Analysis of Gojek Conversations using the NIJ Method and Tools Comparison. Mobile and Forensics, 1(1), pp. 1–8. Universitas Ahmad Dahlan.
• Thamer, N., Alshaya, R., & Hammoudeh, M. A. A. (2024). Reliability and Precision of Digital Forensic Tools and Software: A Systematic Review Study. International Journal of Communication Networks and Information Security, 16(2). https://doi.org/10.17762/ijcnis.v16i2.6679
• Umar, R., Riadi, I., & Zamroni, G. (2017). A Comparative Study of Forensic Tools for WhatsApp Analysis using NIST Measurements. International Journal of Advanced Computer Science and Applications, 8, 69–75. https://doi.org/10.14569/IJACSA.2017.081210
• Nahdli, M., Biddinika, M., & Riadi, I. (2024). Forensic Analysis of the WhatsApp Application Using the National Institute of Justice Framework. International Journal of Advances in Data and Information Systems, 5. https://doi.org/10.59395/ijadis.v5i2.1328
• Kara, I. (2023). Query by Image Examination: Classification of Digital Image-Based Forensics Using Deep Learning Methods. Acta Infologica, 7(2), 348–359. https://doi.org/10.26650/acin.1282567
• Mehta, J., Bhadania, Y., Shah, P., & Prajapati, P. (2024). Comparative Study of Mobile Forensics Tools: Autopsy, Belkasoft X and Magnet Axiom, 1257–1263. https://doi.org/10.1109/ICESC60852.2024.10689971
• Yudhana, A., Fadlil, A., & Setyawan, M. (2020). Analysis of Skype Digital Evidence Recovery Based on Android Smartphones Using the NIST Framework. Jurnal RESTI, 4, 682–690. https://doi.org/10.29207/resti.v4i4.2093
• Leonardo, A., & Indrayani, R. (2022). The Comparison Performance of Digital Forensic Tools Using Additional Root Access Options. Jurnal Ilmiah Teknik Elektro Komputer dan Informatika, 7(3), 512–521. https://doi.org/10.26555/jiteki.v7i3.22381
• Parveen, A., Khan, Z. H., & Ahmad, S. N. (2020). Classification and Evaluation of Digital Forensic Tools. TELKOMNIKA Telecommunication, Computing, Electronics and Control, 18(6), 3096–3106. https://doi.org/10.12928/TELKOMNIKA.v18i6.15295
• Zakarneh, S. K. A. (2024). Mobile Forensic Investigation on iOS & Android Smartphones: Case Study Investigation on WhatsApp. International Journal of Advanced Science and Sustainable Technology, 6(1), 63–98.
• Patel, B., & Mann, P. (2024). A Survey on Mobile Digital Forensic: Taxonomy, Tools, and Challenges. Security and Privacy, 8. https://doi.org/10.1002/spy2.470
• Moreb, M., Ramlawy, I., & Safeia, M. (2022). Evidence Identification Methods for Android and iOS Mobile Devices with Facebook Messenger. In Digital Forensics and Cyber Crime (pp. Chapter 13). https://doi.org/10.1007/978-1-4842-8026-3_13
• Mualfah, D., Syam, M., & Baidarus. (2023). Analisis Perbandingan Tools Mobile Forensic Menggunakan Metode National Institute of Justice (NIJ). Jurnal CoSciTech, 4, 283–292. https://doi.org/10.37859/coscitech.v4i1.4767
• Pangestu, P., & Koprawi, M. (2023). Comparison of Forensic Tool Results on Android Smartphone Backup Files Using NIST Method. Mobile and Forensics, 4, 115–126. https://doi.org/10.12928/mf.v4i2.6496
• Riadi, I., Umar, R., & Syahib, M. (2021). Akuisisi Bukti Digital Viber Messenger Android Menggunakan Metode NIST. Jurnal RESTI, 5, 45–54. https://doi.org/10.29207/resti.v5i1.2626
• Moreb, M. (2022). Mobile Forensics for iOS and Android Platforms: Chrome App Artifacts Depending on SQLite. In Digital Forensics and Cyber Crime (pp. Chapter 14). https://doi.org/10.1007/978-1-4842-8026-3_14
• Gangwar, A. (2022). Twitter Forensics on Android with Belkasoft X. Forensic Focus, 4(1). https://doi.org/10.46293/4n6/2022.02.01.07
• Tamma, R., Mahalik, H. T., & Williams, S. B. (2020). Practical Mobile Forensics (4th ed.). Packt Publishing. ISBN 9781838647520
• Mikhaylov, I. (2016). Mobile Forensics Cookbook: Data Acquisition, Extraction, and Analysis Techniques for iOS, Android, and Windows Phone Devices. Packt Publishing. ISBN 9781785282058
• Harrison, W. (2023). Learn Computer Forensics: A Beginner's Guide to Searching, Analyzing, and Securing Digital Evidence. Packt Publishing. ISBN 9781803238302
• Maras, M.-H. (2017). Windows Forensics Cookbook: Over 80 Recipes to Analyze and Troubleshoot Windows System Issues. Packt Publishing. ISBN 9781784390495
• Oettinger, W. (2023, October 18). Advice for Beginner Computer Forensic Investigators. TechTarget.
• Cruz, V. (2022, November 15). Data Carving Xbox One Using Belkasoft Evidence Center X. eForensics Magazine.