Abstract
Technological advancements have made it possible to use relatively inexpensive hardware and software to replicate and leak sensitive documents. This chapter proposes a novel canary trap method for determining the source of a leaked hard copy document. The method generates self-identifying documents that secretly encode unique information about the individuals who receive them by modifying the inter-word spacing in the original reference document. The encoded information is robust to changes introduced during printing, scanning and copying, rendering the method useful for hard copy as well as digital documents. Due to the lack of publicly-available datasets, a custom hard copy document leakage dataset comprising 100 scanned self-identifying documents encoded at four levels of robustness was created. The hard copy document leakage dataset was subsequently employed to evaluate the performance of the canary trap leak detection method.
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
Preview
Unable to display preview. Download preview PDF.
References
K. Kaneda, H. Kitazawa, K. Iwamura and I. Echizen, A study of equipment dependence of a single-dot-pattern method for information hiding by applying an error-correcting code, Proceedings of the Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 497–501, 2014.
K. Kaneda, F. Nagai, K. Iwamura and S. Hangai, A study of information hiding performance using a simple dot pattern with different tile sizes, Proceedings of the Fourth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 323–326, 2008.
A. Kozachok, S. Kopylov, A. Shelupanov and O. Evsutin, Text marking approach for data leakage prevention, Journal of Computer Virology and Hacking Techniques, vol. 15(3), pp. 219–232, 2019.
V. Kuraki and V. Nakagata, Watermarking technologies for security-enhanced printed documents, Fujitsu Science and Technical Journal, vol. 43(2), pp. 197–203, 2007.
C. Loc, J. Burie and J. Ogier, Stable regions and object-fill-based approach for document image watermarking, Proceedings of the Thirteenth IAPR International Workshop on Document Analysis Systems, pp. 181–186, 2018.
S. Low, N. Maxemchuk, J. Brassil and L. O’Gorman, Document marking and identification using both line and word shifting, Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 2, pp. 853–860, 1995.
J. Nayak, S. Singh, S. Chhabra, G. Gupta and M. Gupta, Detecting data leakage from hard copy documents, in Advances in Digital Forensics XIV, G. Peterson and S. Shenoi (Eds.), Springer, Cham, Switzerland, pp. 111–124, 2018.
I. Safonov, I. Kurilin, M. Rychagov and E. Tolstaya, Embedding digital hidden data into hardcopy, in Document Image Processing for Scanning and Printing, I. Safonov, I. Kurilin, M. Rychagov and E. Tolstaya (Eds.), Springer, Cham, Switzerland, pp. 219–250, 2019.
L. Tan, X. Sun and G. Sun, Print-scan resilient text image watermarking based on stroke direction modulation for Chinese document authentication, Radioengineering, vol. 21(1), pp. 170–181, 2012.
R. Theis, tess-two version 9.1.0, GitHub (github.com/rmtheis/tess-two), 2015.
J. van Beusekom, F. Shafait and T. Breuel, Automatic authentication of color laser print-outs using machine identification codes, Pattern Analysis and Applications, vol. 16(4), pp. 663–678, 2013.
A. Varna, S. Rane and A. Vetro, Data hiding in hard-copy text documents robust to print, scan and photocopy operations, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1397–1400, 2009.
D. Zou and Y. Shi, Formatted text document data hiding robust to printing, copying and scanning, Proceedings of the IEEE International Symposium on Circuits and Systems, vol. 5, pp. 4971–4974, 2005.
ZXing Project Contributors, ZXing 3.4.1, GitHub (github.com/zxing/zxing), 2020.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 IFIP International Federation for Information Processing
About this paper
Cite this paper
Garg, P., Gupta, G., Kumar, R., Sanadhya, S., Gupta, G. (2022). Identifying the Leak Sources of Hard Copy Documents. In: Peterson, G., Shenoi, S. (eds) Advances in Digital Forensics XVIII. DigitalForensics 2022. IFIP Advances in Information and Communication Technology, vol 653. Springer, Cham. https://doi.org/10.1007/978-3-031-10078-9_9
Download citation
DOI: https://doi.org/10.1007/978-3-031-10078-9_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-10077-2
Online ISBN: 978-3-031-10078-9
eBook Packages: Computer ScienceComputer Science (R0)
