Private machine learning classification based on fully homomorphic encryption

Sun, Xiaoqiang; Zhang, Peng; Liu, Joseph K.; Yu, Jianping; Xie, Weixin

doi:10.1109/tetc.2018.2794611

Cited by 83 publications

(69 citation statements)

References 34 publications

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“…x 3 + 2x 2 + 3x + 4 can be further represented by a vector (9,5,15,4). Next, we have (x 3 + 2x 2 + 3x + 4)…”

Section: Plaintext Encodingmentioning

confidence: 99%

“…When compared with non-homomorphic encryptions, it removes the trust on the device and makes us ease to use the computing power of the device. Hence, homomorphic encryption has broad application prospects [5][6][7][8][9][10][11]. In a breakthrough work [12], Gentry demonstrated that fully homomorphic encryption was theoretically possible based on ideal lattices.…”

Section: Introductionmentioning

confidence: 99%

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An Efficient BGV-type Encryption Scheme for IoT Systems

Yuan

Gao

2020

Applied Sciences

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Internet of Thing (IoT) systems usually have less storage and computing power than desktop systems. This paper proposes an efficient BGV-type homomorphic encryption scheme in order fit for secure computing on IoT system. Our scheme reduces the storage space for switch keys and ciphertext evaluation time comparing with previous BGV-type cryptosystems. Specifically, the switch key in homomorphic computations can be a constant but no longer one for each level. Moreover, the product of two ciphertexts can be at the same sublayer as them and the multiplication operations can be repeated between two sublayers. As a result, the multiplication times will not be limited by L in an L-level circuit and, thus, the ciphertext evaluation time will decrease significantly. We implement the scheme with the C language. The performance test shows that the efficiency of the improved scheme is better than Helib in same configurations.

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“…x 3 + 2x 2 + 3x + 4 can be further represented by a vector (9,5,15,4). Next, we have (x 3 + 2x 2 + 3x + 4)…”

Section: Plaintext Encodingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Efficient BGV-type Encryption Scheme for IoT Systems

Yuan

Gao

2020

Applied Sciences

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“…In cloud-based architectures, HE enables performing powerful data analytics in the cloud (Figure 4 (2)) and remote monitoring (Figure 4 (3)) while maintaining data privacy, for example, regarding sensitive medical data [52,53]. It also allows executing ML algorithms in a confidential manner [54]. For example, the authors of [40] presented a multi-key FHE scheme to apply deep learning over data stored in multiple third-party clouds without compromising the confidentiality.…”

Section: Sensor and Actuator Nodes User And Client Platformsmentioning

confidence: 99%

Homomorphic Encryption and Network Coding in IoT Architectures: Advantages and Future Challenges

et al. 2019

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The introduction of the Internet of Things (IoT) is creating manifold new services and opportunities. This new technological trend enables the connection of a massive number of devices among them and with the Internet. The integration of IoT with cloud platforms also provides large storage and computing capabilities, enabling Big Data analytics and bidirectional communication between devices and users. Novel research directions are showing that Network Coding (NC) can increase the robustness and throughput of wireless networks, as well as that Homomorphic Encryption (HE) can be used to perform computations in the cloud while maintaining data privacy.

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“…Many studies on encrypted machine learning have emerged, where homomorphic encryption schemes are adopted for computation on encrypted data. Xiaoqiang Sun et al implemented three private classification algorithms based on homomorphic encryption [42], which were hyperplane decision-based classification, Naïve Bayes classification, and decision tree classification. M Kim et al proposed secure logistic regression for biomedical data [43].…”

Section: Applications Of Homomorphic Encryption Schemesmentioning

confidence: 99%

“…In order to lower the error rate of our scheme, 1 , 2 are set to be as small as possible under the constraints in (35) and (40). Thus 1 is made larger under the constraint (42), which promotes the probability 3 . As discussed in the end of Section 5.1, the error rate of our scheme is…”

Section: Dmmentioning

confidence: 99%

A More Efficient Fully Homomorphic Encryption Scheme Based on GSW and DM Schemes

Wang

Luo

2018

Security and Communication Networks

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Achieving both simplicity and efficiency in fully homomorphic encryption (FHE) schemes is important for practical applications. In the simple FHE scheme proposed by Ducas and Micciancio (DM), ciphertexts are refreshed after each homomorphic operation. And ciphertext refreshing has become a major bottleneck for the overall efficiency of the scheme. In this paper, we propose a more efficient FHE scheme with fewer ciphertext refreshings. Based on the DM scheme and another simple FHE scheme proposed by Gentry, Sahai, and Waters (GSW), ciphertext matrix operations and ciphertext vector additions are both applied in our scheme. Compared with the DM scheme, one more homomorphic NOT AND (NAND) operation can be performed on ciphertexts before ciphertext refreshing. Results show that, under the same security parameters, the computational cost of our scheme is obviously lower than that of GSW and DM schemes for a depth-2 binary circuit with NAND gates. And the error rate of our scheme is kept at a sufficiently low level.

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Private machine learning classification based on fully homomorphic encryption

Cited by 83 publications

References 34 publications

An Efficient BGV-type Encryption Scheme for IoT Systems

An Efficient BGV-type Encryption Scheme for IoT Systems

Homomorphic Encryption and Network Coding in IoT Architectures: Advantages and Future Challenges

A More Efficient Fully Homomorphic Encryption Scheme Based on GSW and DM Schemes

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