2021
DOI: 10.1109/jiot.2020.3014686
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Scalar Product Lattice Computation for Efficient Privacy-Preserving Systems

Abstract: Privacy-preserving applications allow users to perform on-line daily actions without leaking sensitive information. The privacy-preserving scalar product is one of the critical algorithms in many private applications. The state-of-the-art privacy-preserving scalar product schemes use either computationally intensive homomorphic (public-key) encryption techniques such as Paillier encryption to achieve strong security (i.e., 128−bit) or random masking technique to achieve high efficiency for low security. In thi… Show more

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Cited by 8 publications
(5 citation statements)
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References 39 publications
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“…To compare the computational costs, we calculated the number of time-consuming operations during session key agreement in the pairing-based protocols [28,29,39] and the proposed LIAMKA scheme. Based on the results in Rahulamathavan and others [42], we chose the parameters of these schemes for 80-bit security. Because the pairingbased protocol [28,29,39] generates only four session keys in one run, the time required is the total time of two runs for the generation of eight session keys.…”
Section: Performance Analysismentioning
confidence: 99%
“…To compare the computational costs, we calculated the number of time-consuming operations during session key agreement in the pairing-based protocols [28,29,39] and the proposed LIAMKA scheme. Based on the results in Rahulamathavan and others [42], we chose the parameters of these schemes for 80-bit security. Because the pairingbased protocol [28,29,39] generates only four session keys in one run, the time required is the total time of two runs for the generation of eight session keys.…”
Section: Performance Analysismentioning
confidence: 99%
“…An encryption scheme with the above FHE properties was invented by Craig Gentry in 2009 [13]. The scheme is based on Lattice-based cryptography hence secure against attacks arising from quantum computers [14]- [16]. Since Gentry's ground breaking work, there are numerous improvements were made by several researchers to improve efficiency and scalability.…”
Section: Fully Homomorphic Encryptionmentioning
confidence: 99%
“…Semi-trusted • Laplace mechanism Enhanced differential privacy (AI-empowered) Challenge to detect the changes of particular values [249] Homomorphic encryption…”
Section: B State-of-the-art Privacy Preservation Techniques and Visio...mentioning
confidence: 99%
“…Finally, another name of data obfuscation, data masking protects personal data by hiding identifiable information with modified content. Some state-the-art studies [249] found that the combination of homomorphic encryption and data masking can be a perfect way to provide a high degree of security against quantum attacks, which are taken to appear in 6G, while still maintain privacy at best.…”
Section: B State-of-the-art Privacy Preservation Techniques and Visio...mentioning
confidence: 99%