A robust reversible watermarking technique based on prediction error expansion using ECC

2017 ◽  
Author(s):  
Jinal H. Mehta ◽  
Vishakha Kelkar ◽  
Kushal Tuckley
Keyword(s):  
Prediction Error ◽  
Reversible Watermarking ◽  
Prediction Error Expansion ◽  
Error Expansion

scholarly journals Reversible Fragile Watermarking Scheme for Relational Database Based on Prediction-Error Expansion

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ali Hamadou ◽  
Lanciné Camara ◽  
Abdoul Aziz Issaka Hassane ◽  
Harouna Naroua
Keyword(s):  
Prediction Error ◽  
Relational Databases ◽  
Database Systems ◽  
Original Data ◽  
Research Direction ◽  
Reversible Watermarking ◽  
Tamper Localization ◽  
Integrity Checking ◽  
Prediction Error Expansion ◽  
Error Expansion

The protection of database systems content using digital watermarking is nowadays an emerging research direction in information security. In the literature, many solutions have been proposed either for copyright protection and ownership proofing or integrity checking and tamper localization. Nevertheless, most of them are distortion embedding based as they introduce permanent errors into the cover data during the encoding process, which inevitably affect data quality and usability. Since such distortions are not tolerated in many applications, including banking, medical, and military data, reversible watermarking, primarily designed for multimedia content, has been extended to relational databases. In this article, we propose a novel prediction-error expansion based on reversible watermarking strategy, which not only detects and localizes malicious modifications but also recovers back the original data at watermark detection. The effectiveness of the proposed method is proved through rigorous theoretical analysis and detailed experiments.

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