Collusion-resistant reversible data hiding in encrypted domains (CR-RDHEI): A robust framework combining cross-domain neural prediction with divisor secret sharing and adaptive shape coding
Key Points
Data hiding is enhanced using a collusion-resistant design and neural predictions, ensuring security.
Key metrics indicate that the framework is effective in managing encrypted data across multiple domains.
Assessment using a novel combination of cross-domain neural prediction and divisor secret sharing methods shows promising results.
Highlights the importance of combining advanced data protection techniques to defend against potential attacks.
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Collusion-resistant reversible data hiding in encrypted domains (CR-RDHEI): A robust framework combining cross-domain neural prediction with divisor secret sharing and adaptive shape coding | Synapse