Low-Complexity VLSI Design of Large Integer Multipliers for Fully Homomorphic Encryption

Ye, Jheng-Hao; Shieh, Ming-Der

doi:10.1109/tvlsi.2018.2829539

Cited by 20 publications

(8 citation statements)

References 15 publications

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“…When there is no ambiguity, G(L, K) is referred as G for easy writing. In (17), Q is the augmented version of G and the size of Q is 1x(L+K+2), because two extra elements are appended to Q. Element R is the randomizing element and S is the signature element.…”

Section: Encryption Of Datamentioning

confidence: 99%

“…Consider the case where scalars R and S are not introduced in forming Q from G as in (17). Then Q = G. Further, consider the scenario where G is an all zero vector when the corresponding g = 0 of size Then Q is also an all zero vector and the encrypted value of Q represented by C as given by (19) would also be an all zero vector.…”

Section: Role Of R and S In Homomorphic Encryption/decryptionmentioning

confidence: 99%

“…HPR method is computationally expensive. In [17], [18], authors have discussed on FPGA based fully homomorphic encryptions. They have provided solutions for achieving low-complexity homomorphic operations for FHE, converging on the hardware implementation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A novel secure biomedical data aggregation using fully homomorphic encryption in WSN

Chethana

Padmaja

2021

IJEECS

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A new method of secure data aggregation for decimal data having integer as well as fractional part using homomorphic encryption is described. The proposed homomorphic encryption provides addition, subtraction, multiplication, division and averaging operations in the cipher domain for both positive and negative numbers. The scheme uses integer matrices in finite field Zp as encryption and decryption keys. An embedded Digital signature along with data provides data integrity and authentication by signature verification at the receiving end. The proposed scheme is immune to chosen plaintext and chosen ciphertext attacks. In the case of homomorphic multiplication, the ciphertext expansion ratio grows linearly with the data size. The computational complexity of the proposed method for multiplication and division is relatively less by 22.87% compared to Brakerski and Vaikantanathan method when the size of the plaintext data is ten decimal digits.

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Section: Encryption Of Datamentioning

confidence: 99%

Section: Role Of R and S In Homomorphic Encryption/decryptionmentioning

confidence: 99%

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A novel secure biomedical data aggregation using fully homomorphic encryption in WSN

Chethana

Padmaja

2021

IJEECS

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“…The N mul of multiplication unit in our implementation scheme is 2 786432 −1, so the sub-block size γ can be chosen as 756839 (2 756839 − 1 is the 32nd Mersenne prime). The largest number multiplication unit on FPGA as we know is the module in [15], and its N mul = 2 1179648 − 1. Therefore, the largest γ can be 859433 (2 859433 −1 is the 33rd Mersenne prime).…”

Section: B Key Parameter Calculation Of Large-scale Pa Schemementioning

confidence: 99%

Large-scale and High-speed Privacy Amplification for FPGA-based Quantum Key Distribution

Yan¹,

Li²,

Mao³

2021

Preprint

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The FPGA-based Quantum key distribution (QKD) system is an important trend of QKD systems. It has several advantages, real time, low power consumption and high integration density. Privacy amplification is an essential part in a QKD system to ensure the security of QKD. Existing FPGAbased privacy amplification schemes have an disadvantage, that the throughput and the input size of these schemes (the best scheme 116M bps@10 6 ) are much lower than these on other platforms (the best scheme 1Gbps@10 8 ). This paper designs a new PA scheme for FPGA-based QKD with multilinear modular hash-modular arithmetic hash (MMH-MH) PA and number theoretical transform (NTT) algorithm. The new PA scheme, named large-scale and high-speed (LSHS) PA scheme, designs a multiplication-reusable architecture and three key units to improve the performance. This scheme improves the input size and throughput of PA by above an order of magnitude. The throughput and input size of this scheme (1Gbps@10 8 ) is at a comparable level with these on other platforms.

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“…A new FHE scheme based on integers [11] swamped the above said intricacy. Later many mutated integer and Linear Algebra based schemes [12] - [17] are introduced.…”

Section: A Literature Survey the Fully Homomorphic Encryption Systemsmentioning

confidence: 99%

Privacy Preserving Outsourced Calculations With Symmetric Fully Homomorphic Encryption

Umadevi,

Gopalan

2019

IJITEE

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Cloud computing is a new paradigm which provides cloud storage service to manage, maintain and back up private data remotely. For privacy concerns the data is kept encrypted and made available to users on demand through cloud service provider over the internet. The legacy encryption techniques rely on sharing of keys, so service providers and end users of the cloud have exclusive rights on the data thus the secrecy may loss. Homomorphic Encryption is a significant encryption technique which allows users to perform limited arithmetic on the enciphered data without loss of privacy and security. This paper addresses a new simple and non-bootstrappable Fully Homomorphic Encryption Scheme based on matrices as symmetric keys with access control.

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Low-Complexity VLSI Design of Large Integer Multipliers for Fully Homomorphic Encryption

Cited by 20 publications

References 15 publications

A novel secure biomedical data aggregation using fully homomorphic encryption in WSN

A novel secure biomedical data aggregation using fully homomorphic encryption in WSN

Large-scale and High-speed Privacy Amplification for FPGA-based Quantum Key Distribution

Privacy Preserving Outsourced Calculations With Symmetric Fully Homomorphic Encryption

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