Forgery Detection of Documents: A Review in Digital Forensics
Abstract
The current technological age is witnessing a great revolution in the development of software applications. These applications are widely used for various purposes, especially digital documents processing. Several applications are available for general use as they allow creating and modifying documents digitally. In this context, there are many illegal aspects when using such applications. For instance, they can be used in unauthorized manipulation of official documents, which makes it a punishable crime by law. The science of digital forensics integrates the field of criminal and the computer science through providing several methods that can be followed for the purpose of detecting forgery or testing forged documents. This study conducted a survey of the latest methods used to detect forgery, which is of a great benefit to the investigators in the judiciary in general, as well as in the field of digital forensics in particular. This work reviews the most prominent advantages of each method that will be of benefit to researchers and workers in this field.
References
- Aboul-Enein, Y, .I Gh TANASE, Andrei A BUNACIU, and Florin Mihai UDRIcSTIOIU. Application of Micro-Raman and FT-IR Spectroscopy in Forensic Analysis of Questioned Documents. Gazi University Journal of Science 25, no. 2 (2012): 37175.
- Afchar, Darius, Vincent Nozick, Junichi Yamagishi, and Isao Echizen. Mesonet: A Compact Facial Video Forgery Detection Network. In 2018 IEEE International Workshop on Information Forensics and Security (WIFS), 17, 2018.
- Al-Qershi, Osamah M, and Bee Ee Khoo. Passive Detection of Copy-Move Forgery in Digital Images: State-of-the-Art. Forensic Science International 231, no. 13 (2013): 28495.
- Al-Sanjary, Omar Ismael, and Ghazali Sulong. Detection of Video Forgery: A Review of Literature. Journal of Theoretical & Applied Information Technology 74, no. 2 (2015).
- Aloraini, Mohammed, Mehdi Sharifzadeh, and Dan Schonfeld. Sequential and Patch Analyses for Object Removal Video Forgery Detection and Localization. IEEE Transactions on Circuits and Systems for Video Technology, 2020.
- Aloraini, Mohammed, Mehdi Sharifzadeh, Chirag Agarwal, and Dan Schonfeld. Statistical Sequential Analysis for Object-Based Video Forgery Detection. Electronic Imaging 2019, no. 5 (2019): 54143.
- Alshayeji, Mohammad H, Mohammad Al-Rousan, and Dunya T Hassoun. Detection Method for Counterfeit Currency Based on Bit-Plane Slicing Technique. International Journal of Multimedia and Ubiquitous Engineering 10, no. 11 (2015): 22542.
- Ameh, Paul Ocheje, and Musa Suud Ozovehe. Forensic Examination of Inks Extracted from Printed Documents Using Fourier Transform Infrared Spectroscopy. Edelweiss Applied Science and Technology 2, no. 1 (2018): 1017.
- Anand, Vijay, Mohammad Farukh Hashmi, and Avinash G Keskar. A Copy Move Forgery Detection to Overcome Sustained Attacks Using Dyadic Wavelet Transform and SIFT Methods. In Asian Conference on Intelligent Information and Database Systems, 53042, 2014.