Reversible watermarking schemes for relational database are usually classified into two groups: robust schemes and fragile schemes. The main limitation of existing reversible fragile methods is that they cannot differentiate between legal and malicious modifications. In this paper, we introduce a novel lossless semi-fragile scheme based on prediction-error expansion for content protection of relational database. In the proposed method, all attributes in a database relation are first classified according to their sensitivity to legitimate updates. Then, the watermark is embedded by expanding the prediction error of the two least significant digits of securely selected attributes. At watermark extraction, the proposed method has the ability to fully restore the original data while detecting and localizing tampering. The applicability of our method is demonstrated theoretically and experimentally.
References
[1]
Aberna, P. and Agilandeeswari, L. (2023) Digital Image and Video Watermarking: Methodologies, Attacks, Applications, and Future Directions. Multimedia Tools and Applications, 83, 5531-5591. https://doi.org/10.1007/s11042-023-15806-y
[2]
Gao, Z.Z., Cheng, Y. and Yin, Z.X. (2024) Fragile Model Watermarking: A Comprehensive Survey of Evolution, Characteristics, and Classification.
[3]
Rani, S. and Halder, R. (2022) Comparative Analysis of Relational Database Watermarking Techniques: An Empirical Study. IEEE Access, 10, 27970-27989. https://doi.org/10.1109/access.2022.3157866
[4]
Hamadou, A., Sun, X., Gao, L. and Shah, S.A. (2011) A Fragile Zero-Watermarking Technique for Authentication of Relational Databases. International Journal of Digital Content Technology and its Applications, 5, 189-200. https://doi.org/10.4156/jdcta.vol5.issue5.21
[5]
Camara, L., Li, J., Li, R. and Xie, W. (2014) Distortion-Free Watermarking Approach for Relational Database Integrity Checking. Mathematical Problems in Engineering, 2014, 1-10. https://doi.org/10.1155/2014/697165
[6]
Camara, L., Coulibaly, D., Hamadou, A. and Li, J. (2017) An Effective Approach for Non-Numeric Relational Database Verification. International Journal of Database Theory and Application, 10, 35-46. https://doi.org/10.14257/ijdta.2017.10.6.03
[7]
Gao, L., Wang, D. and Hamadou, A. (2013) New Fragile Database Watermarking Scheme with Restoration Using Reed-Solomon Codes. Journal of Computational and Theoretical Nanoscience, 10, 147-153. https://doi.org/10.1166/jctn.2013.2671
[8]
Li, D., Ma, C., Gao, H. and Jin, X. (2023) LBP Feature and Hash Function Based Dual Watermarking Algorithm for Database. Data & Knowledge Engineering, 148, Article 102228. https://doi.org/10.1016/j.datak.2023.102228
[9]
Lin, C., Nguyen, T. and Chang, C. (2021) LRW-CRDB: Lossless Robust Watermarking Scheme for Categorical Relational Databases. Symmetry, 13, Article 2191. https://doi.org/10.3390/sym13112191
[10]
Hou, R., Xian, H., Wang, X. and Li, J. (2019) A Robust Reversible Watermarking Scheme for Relational Data. In: Li, J., Liu, Z.L. and Peng, H., Eds., Security and Privacy in New Computing Environments, Springer, 545-550. https://doi.org/10.1007/978-3-030-21373-2_44
[11]
Hu, D., Zhao, D. and Zheng, S. (2019) A New Robust Approach for Reversible Database Watermarking with Distortion Control. IEEE Transactions on Knowledge and Data Engineering, 31, 1024-1037. https://doi.org/10.1109/tkde.2018.2851517
[12]
Chang, C., Nguyen, T. and Lin, C. (2013) A Blind Reversible Robust Watermarking Scheme for Relational Databases. The Scientific World Journal, 2013, Article 717165. https://doi.org/10.1155/2013/717165
[13]
Arif Shah, S., Ali Khan, I., Hassan Kazmi, S.Z. and Binti Md Nasaruddin, F.H. (2021) Semi-Fragile Watermarking Scheme for Relational Database Tamper Detection. Malaysian Journal of Computer Science, 34, 1-12. https://doi.org/10.22452/mjcs.vol34no1.1
[14]
Hamadou, A., Sun, X., Shah, S. and Gao, L. (2011) A Weight-Based Semi-Fragile Watermarking Scheme for Integrity Verification of Relational Data. International Journal of Digital Content Technology and its Applications, 5, 148-157. https://doi.org/10.4156/jdcta.vol5.issue8.17
[15]
Murugan, R., John, A.T. and Ibrahim, S. (2020) A Semi-Fragile Watermarking Scheme for Integrity Checking of Relational Databases. International Journal of Recent Technology and Engineering, 8, 806-812. https://doi.org/10.35940/ijrte.f6996.038620
[16]
Franco-Contreras, J., Coatrieux, G., Cuppens, F., Cuppens-Boulahia, N. and Roux, C. (2014) Robust Lossless Watermarking of Relational Databases Based on Circular Histogram Modulation. IEEE Transactions on Information Forensics and Security, 9, 397-410. https://doi.org/10.1109/tifs.2013.2294240
[17]
Franco Contreras, J., Coatrieux, G., Chazard, E., Cuppens, F., Cuppens-Boulahia, N. and Roux, C. (2012) Robust Lossless Watermarking Based on Circular Interpretation of Bijective Transformations for the Protection of Medical Databases. 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, 28 August-1 September 2012, 5875-5878. https://doi.org/10.1109/embc.2012.6347330
[18]
Unnikrishnan, K. and Pramod, K.V. (2017) Robust Optimal Position Detection Scheme for Relational Database Watermarking through HOLPSOFA Algorithm. Journal of Information Security and Applications, 35, 1-12. https://doi.org/10.1016/j.jisa.2017.04.005
[19]
Khanduja, V. and Chakraverty, S. (2018) Fragile Watermarking of Decision System Using Rough Set Theory. Arabian Journal for Science and Engineering, 43, 7621-7633. https://doi.org/10.1007/s13369-018-3120-7
[20]
Hamadou, A., Camara, L., Issaka Hassane, A.A. and Naroua, H. (2020) Reversible Fragile Watermarking Scheme for Relational Database Based on Prediction-Error Expansion. Mathematical Problems in Engineering, 2020, 1-9. https://doi.org/10.1155/2020/1740205
[21]
Thodi, D.M. and Rodriguez, J.J. (2004) Prediction-Error Based Reversible Watermarking. 2004 International Conference on Image Processing, Singapore, 24-27 October 2004, 1549-1552. https://doi.org/10.1109/icip.2004.1421361
[22]
Ferguson, N. and Schneier, B. (2003) Practical Cryptography. Wiley.
