In the study of content authentication and tamper detection of digital text documents, a novel English text zero-watermarking approach based on probabilistic patterns proposed in this paper. Hidden Markov model was presented, and the core algorithm of the watermark generation and detection was designed in this paper. In the proposed approach, Hidden Markov model letter-level based of order one was constructed for text analysis and watermark generation based on interrelationship between contents of host text document by using the two-dimensional matrix coordinate of probabilistic weights of states and transitions. However, we can extracted this watermark later using extraction and detection algorithm to identify the status of text document such as authentic, tampered, etc. Furthermore, the effectiveness and feasibility of our proposed algorithm was proved with algorithm experiments and comparative with other recently approach under random insertion and deletion attacks in localized and dispersed form on 6 text datasets of varying length. Results showed that our proposed algorithm is more secure, had better robustness, and always detects tampering attacks occurred randomly on text even when the tampering volume is low or high.

1. Z. JaliI, A. Hamza, S. Shahidm M. Arif, A. Mirza, A Zero Text Watermarking Algorithm based on Non-Vowel ASCII Characters. International Conference on Educational and Information Technology (ICET 2010), IEEE.
2. Suhail M. A. , Digital Watermarking for Protection of Intellectual Property. A Book Published by University of Bradford, UK, 2008.
3. L. Robert, C. Science, C. Government Arts, A Study on Digital Watermarking Techniques. International Journal of Recent Trends in Engineering, Vol. 1, No. 2, pp. 223-225, 2009.
4. X. Zhou, S. Wang, S. Xiong, Security Theory and Attack Analysis for Text Watermarking. International Conference on E-Business and Information System Security, IEEE, pp. 1-6, 2009.
5. T. Brassil, S Low, and N. F. Maxemchuk, Copyright Protection for the Electronic Distribution of Text Documents. Proceedings of the IEEE, vol. 87, no. 7, July 1999, pp. 1181-1196.
6. M. Atallah, V. Raskin, M. C. Crogan, C. F. Hempelmann, F. Kerschbaum, D. Mohamed, and S. Naik, Natural language watermarking: Design, analysis, implementation. and Proceedings of the a Fourth Hiding Workshop, vol. LNCS 2137, 25-27 , 2001.
7. N. F. Maxemchuk and S Low, Marking Text Documents. Proceedings of the IEEE International Conference on Image Processing, Washington, DC, Oct 26-29, 1997, pp. 13- 16.
8. D. Huang, H. Yan, Interword distance changes represented by sine waves for watermarking text images. IEEE Trans. Circuits and Systems for Video Technology, Vol. 11, No. 12, pp. 1237 1245, 2001.
9. N. Maxemchuk, S. Low, Performance Comparison of Two Text Marking Methods. IEEE Journal of Selected Areas in Communications (JSAC), vol. 16 no. 4, pp. 561-572, 1998.
10. S. Low, N. Maxemchuk, Capacity of Text Marking Channel. IEEE Signal Processing Letters, vol. 7, no. 12 , pp. 345 -347, 2000.
11. M. Kim, Text Watermarking by Syntactic Analysis. 12th WSEAS International Conference on Computers, Heraklion, Greece, 2008.
12. H. Meral, B. Sankur, A. Sumru, T. Güngör, E. Sevinç , Natural language watermarking via morphosyntactic alterations. Computer Speech and Language, 23, pp. 107-125, 2009.
13. Z. Jalil, A. Mirza, A Review of Digital Watermarking Techniques for Text Documents. International Conference on Information and Multimedia Technology, pp. 230-234 , IEEE, 2009.
14. M. AtaIIah, C. McDonough, S. Nirenburg, V. Raskin, Natural Language Processing for Information Assurance and Security: An Overview and Implementations. Proceedings 9th ACM/SIGSAC New Security Paradigms Workshop, pp. 5 1-65, 2000.
15. H. Meral, E. Sevinc, E. Unkar, B. Sankur, A. Ozsoy, T. Gungor, Syntactic tools for text watermarking. In Proc. of the SPIE International Conference on Security, Steganography, and Watermarking of Multimedia Contents, pp. 65050X-65050X-12, 2007.
16. O. Vybornova, B. Macq. , Natural Language Watermarking and Robust Hashing Based on Presuppositional Analysis. IEEE International Conference on Information Reuse and Integration, IEEE, 2007.
17. M. tallah, V. Raskin, C. Hempelmann, language watermarking and tamperproofing. Proc. of al. . Natural 5th International Information Hiding Workshop, Noordwijkerhout, Netherlands, pp. 196-212, 2002.
18. U. Topkara, M. Topkara, M. J. Atallah, The Hiding Virtues of Ambiguity: Quantifiably Resilient Watermarking of Natural Language Text through Synonym Substitutions. In Proceedings of ACM Multimedia and Security Conference, Geneva, 2006.
19. Z Jalil, A. Mirza, H. Jabeen, Word Length Based Zero-Watermarking Algorithm for Tamper Detection in Text Documents. 2nd International Conference on Computer Engineering and Technology, pp. 378-382, IEEE, 2010.
20. Z Jalil, A. Mirza, M. Sabir, Content based Zero-Watermarking Algorithm for Authentication of Text Documents. (IJCSIS) International Journal of Computer Science and Information Security, Vol. 7, No. 2, 2010.
21. Z. Jalil , A. Mirza, T. Iqbal, A Zero-Watermarking Algorithm for Text Documents based on Structural Components. pp. 1-5 , IEEE, 2010.
22. S. Ranganathan, A. Johnsha, K. Kathirvel, M. Kumar, Combined Text Watermarking. International Journal of Computer Science and Information Technologies, Vol. 1 (5), pp. 414-416, 2010.

Digital Watermarking Hidden Markov Model