Low distortion reversible database watermarking based on hybrid intelligent algorithm.

Area of Science:

• Computer Science
• Information Security
• Data Management

Background:

• Databases are crucial for information sharing but vulnerable to theft and misuse, causing copyright and privacy issues.
• Reversible watermarking secures relational databases, verifying ownership and enabling data recovery.
• Existing methods often compromise data integrity or offer insufficient protection against attacks.

Purpose of the Study:

• To propose a robust and reversible database watermarking technique.
• To achieve a better balance between data protection and data recovery.
• To enhance the security of shared relational databases.

Main Methods:

• Utilizing a hash function for grouping digital relational databases.
• Implementing a band weight function to control data distortion and watermarking capacity.
• Employing firefly algorithms (FA) and simulated annealing algorithms (SA) for efficient watermark embedding.
• Embedding watermarks using differential expansion.

Main Results:

• The proposed method effectively maintains data quality.
• Demonstrated good robustness against malicious attacks.
• Achieved a balance between data protection and recovery capabilities.

Conclusions:

• The developed watermarking technique offers a viable solution for securing relational databases.
• It provides robust protection against attacks while preserving data integrity.
• This method enhances the security and trustworthiness of shared data systems.