Provable Data Possession using Additive Homomorphic Encryption

Shah, Parth; Prajapati, Priteshkumar

doi:10.1016/j.jksuci.2020.09.003

Cited by 7 publications

(2 citation statements)

References 12 publications

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“…This result, when decrypted, is the same as if the same operations had been performed on the original data. This technology has long been a research hotspot in the fields of cryptography and data security [24,25].…”

Section: Homomorphic Encryptionmentioning

confidence: 99%

“…After numerous experiments, it can be concluded that when r ≈ 2 √ η , q ≈ 2 η 3 , the system exhibits better stability and the encryption effect is also optimal. Byte(q)∈[220, 2077) Byte(q)∈[2077, 7388) Byte(q)∈[7388, 25,807) Byte(q)∈ [25,807,65,443) Figure 8. The effect of Byte(q) on the accuracy for η = 9.…”

Section: Impact Factor For Pdphe (Rq3)mentioning

confidence: 99%

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PDPHE: Personal Data Protection for Trans-Border Transmission Based on Homomorphic Encryption

Liu,

Yang,

Liu

et al. 2024

Electronics

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In the digital age, data transmission has become a key component of globalization and international cooperation. However, it faces several challenges in protecting the privacy and security of data, such as the risk of information disclosure on third-party platforms. Moreover, there are few solutions for personal data protection in cross-border transmission scenarios due to the difficulty of handling sensitive information between different countries and regions. In this paper, we propose an approach, personal data protection based on homomorphic encryption (PDPHE), to creatively apply the privacy computing technology homomorphic encryption (HE) to cross-border personal data protection. Specifically, PDPHE reconstructs the classical full homomorphic encryption (FHE) algorithm, DGHV, by adding support for multi-bit encryption and security level classification to ensure consistency with current data protection regulations. Then, PDPHE applies the reconstructed algorithm to the novel cross-border data protection scenario. To evaluate PDPHE in actual cross-border data transfer scenarios, we construct a prototype model based on PDPHE and manually construct a data corpus called PDPBench. Our evaluation results on PDPBench demonstrate that PDPHE cannot only effectively solve privacy protection issues in cross-border data transmission but also promote international data exchange and cooperation, bringing significant improvements for personal data protection during cross-border data sharing.

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Section: Homomorphic Encryptionmentioning

confidence: 99%

Section: Impact Factor For Pdphe (Rq3)mentioning

confidence: 99%