Abstract
With the growth of Information and Communication Technology, data sharing plays a pivotal role in all parts of the Internet. A major issue that needs to be tackled urgently is to protect the ownership of data during the sharing process. Digital watermarking technology is a major solution to ownership protection. Many reversible watermarking approaches are proposed to achieve the function of ownership protection, but most methods can only resist malicious attacks to a certain extent and can not regenerate the complete watermarks in case part of watermarks are destroyed. In this paper, a robust and reversible watermarking technique (RRWEC) applied in relational database has been proposed, which utilizes the Erasure Codes Technique and watermarking in groups. The watermarks embedded into data come from meaningful characters of identification information of a database owner. The grouping method based on clustering, without dependent primary keys, is utilized to group the data, which can resist attacks on the data structure. The erasure code technique is devised to regenerate the complete watermarking information when some sub-watermarks embedded into data are maliciously modified or removed. The results of experiments verify the effectiveness and robustness of RRWEC against malicious attacks, such as data structure attack, subset addition attack, subset alteration and deletion attack, and show that when half of the watermarks are destroyed, the watermark regeneration algorithm can still recover the complete watermarking information.
Supported by The National Key Research and Development Program of China (No. 2017YFB0803002), Key Research and Development Program of Guangdong Province (No. 2019B010136003), Peng Cheng Laboratory Project of Guangdong Province (PCL2018KP004).
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Chai, H., Yang, S., Jiang, Z.L., Wang, X., Chen, Y., Luo, H. (2020). A New Robust and Reversible Watermarking Technique Based on Erasure Code. In: Wen, S., Zomaya, A., Yang, L. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2019. Lecture Notes in Computer Science(), vol 11944. Springer, Cham. https://doi.org/10.1007/978-3-030-38991-8_11
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