Preserving Privacy for Blockchain-driven Image Watermarking using Fully Homomorphic Encryption

Basuki, Akbari Indra; Setiawan, Iwan; Rosiyadi, Didi

doi:10.1145/3489088.3489130

Cited by 3 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The use of CKKS homomorphic encryption is to ensure the secrecy of watermarking approval with better efficiency than existing works [16], [17], [25]. The data for watermark embedding is openly available in the blockchain ledger in an encrypted format.…”

Section: Blockchain-based Watermarking Servicementioning

confidence: 99%

See 1 more Smart Citation

Approximation-based homomorphic encryption for secure and efficient blockchain-driven watermarking service

Rosiyadi

Basuki

Ramdhani

et al. 2023

IJECE

View full text Add to dashboard Cite

<p>Homomorphic encryption has been widely used to preserve the privacy of watermarking process on blockchain-driven watermarking services. It offers transparent and traceable encrypted watermarking without revealing sensitive data such as original images or watermark data to the public. Nevertheless, the existing works suffer from enormous memory storage and extensive computing power. This study proposed an approximation-based homomorphic encryption for resource-efficient encrypted watermarking without sacrificing watermarking quality. We demonstrated the efficiency of the Cheon-Kim-Kim-Son (CKKS) encrypted watermarking process using discrete cosine transform-singular value decomposition (DCT-SVD) embedding. The evaluation results showed that it could preserve the watermarking quality similar to non-encrypted watermark embedding, even after geometrical and filtering attacks. Compared to existing homomorphic encryption, such as Brakerski-Gentry-Vaikuntanathan (BFV) encryption, it has superior performance regarding resource utilization and watermarking quality preservation.</p>

show abstract

Section: Blockchain-based Watermarking Servicementioning

confidence: 99%

“…− The authority computes watermark similarity and its quality by comparing the extracted watermark. − (W"A) with the original watermark (W) using SSIM (15) and NC (16) values. − The authority submits the validation result to the blockchain upon computing the values.…”

Section: Ckks-encrypted Watermarking Verificationmentioning

confidence: 99%