Privacy-Preserving Feature Selection with Fully Homomorphic Encryption

For the feature selection problem, we propose an efficient privacy-preserving algorithm. Let D, F, and C be data, feature, and class sets, respectively, where the feature value

x (F_{i})

and the class label

x (C)

are given for each

x \in D

and

F_{i} \in F

. For a triple

(D, F, C)

, the feature selection problem is to find a consistent and minimal subset

F^{'} \subseteq F

, where ‘consistent’ means that, for any

x, y \in D

x (C) = y (C)

x (F_{i}) = y (F_{i})

for

F_{i} \in F^{'}

, and ‘minimal’ means that any proper subset of

F^{'}

is no longer consistent. On distributed datasets, we consider feature selection as a privacy-preserving problem: assume that semi-honest parties

A

and

B

have their own personal

D_{A}

and

D_{B}

. The goal is to solve the feature selection problem for

D_{A} \cup D_{B}

without sacrificing their privacy. In this paper, we propose a secure and efficient algorithm based on fully homomorphic encryption, and we implement our algorithm to show its effectiveness for various practical data. The proposed algorithm is the first one that can directly simulate the CWC (Combination of Weakest Components) algorithm on ciphertext, which is one of the best performers for the feature selection problem on the plaintext. View Full-Text

Keywords: CWC algorithm; oblivious sorting; TFHE; IND-CPA

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MDPI and ACS Style

Ono, S.; Takata, J.; Kataoka, M.; I, T.; Shin, K.; Sakamoto, H. Privacy-Preserving Feature Selection with Fully Homomorphic Encryption. Algorithms 2022, 15, 229. https://doi.org/10.3390/a15070229

AMA Style

Ono S, Takata J, Kataoka M, I T, Shin K, Sakamoto H. Privacy-Preserving Feature Selection with Fully Homomorphic Encryption. Algorithms. 2022; 15(7):229. https://doi.org/10.3390/a15070229

Chicago/Turabian Style

Ono, Shinji, Jun Takata, Masaharu Kataoka, Tomohiro I, Kilho Shin, and Hiroshi Sakamoto. 2022. "Privacy-Preserving Feature Selection with Fully Homomorphic Encryption" Algorithms 15, no. 7: 229. https://doi.org/10.3390/a15070229

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