Abstract
Copy-move is one type of attack to forge a digital image where the attacker duplicates several areas of the image and paste them in different places to conceal a particular object on the original image. After the forgery, advanced methods such as noise addition and blurring, are often performed in the forged image to make it more challenging to recognize the attack. Therefore, it is required to do a preprocessing before conducting the detection. The preprocessing can be eliminated using a copy-move detection that is more resistant to noise addition and blurring. This paper proposes a new, flexible, and robust method that perform forensic analysis of both regular and advanced copy-move using modification and addition from two methods. The first method is designed to identify a regular copy-move attack, while the second one is effective for an advanced attack. The proposed method combines these two methods, can adapt to the forged image condition, and no preprocessing is required.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abdel-Basset, M., Manogaran, G., Fakhry, A.E., El-Henawy, I.: 2-Levels of clustering strategy to detect and locate copy-move forgery in digital images. Multimed. Tools Appl. 79(7), 5419–5437 (2020)
Abidin, A.B.Z., Majid, H.B.A., Samah, A.B.A., Hashim, H.B.: Copy-move image forgery detection using deep learning methods: a review. In: Proceedings of the 6th International Conference on Research and Innovation in Information Systems, pp. 1–6 (2019)
Christlein, V., Riess, C., Jordan, J., Riess, C., Angelopoulou, E.: An evaluation of popular copy-move forgery detection approaches. IEEE Trans. Inf. Forensics Secur. 7(6), 1841–1854 (2012)
Fridrich, A.J., Soukal, B.D., Lukáš, A.J.: Detection of copy-move forgery in digital images. In: Proceedings of the Digital Forensic Research Workshop (2003)
Luo, W., Huang, J., Qiu, G.: Robust detection of region-duplication forgery in digital image. In: Proceedings of the 18th International Conference on Pattern Recognition, pp. 746–749 (2006)
Mirror Board: Sorry. we were hoaxed. Daily Mirror Newspaper (2004)
Ng, T.T., Chang, S.F.: A model for image splicing. Proc. Int. Conf. Image Processing. 2, 1169–1172 (2004)
Popescu, A.C., Farid, H.: Exposing digital forgeries by detecting duplicated image regions. Technical. Rep. TR2004-515, Department of Computer Science, Dartmouth College (2004)
Popescu, A.C., Farid, H.: Exposing digital forgeries by detecting traces of resampling. IEEE Trans. Signal Process. 53(2), 758–767 (2005)
Vogan, D.: Lexicographic order. Technical report, Department of Mathematics, Massachusetts Institute of Technology. http://www-math.mit.edu/~dav/lex2.pdf
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Studiawan, H., Salimi, R.N., Ahmad, T. (2021). Forensic Analysis of Copy-Move Attack with Robust Duplication Detection. In: Abraham, A., et al. Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020). SoCPaR 2020. Advances in Intelligent Systems and Computing, vol 1383. Springer, Cham. https://doi.org/10.1007/978-3-030-73689-7_39
Download citation
DOI: https://doi.org/10.1007/978-3-030-73689-7_39
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-73688-0
Online ISBN: 978-3-030-73689-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)