A Gini Coefficient Measurement Method of Income Distribution Gap Based on Privacy-preservation
Yitong Wang, Bai Liu, Xiangyi Zhang, Runhua Shi, Mingwu Zhang · 2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP) · 2021
Aiming at the research on individual income distribution gap in the field of Economics, this paper presents a Gini Coefficient measurement method of income distribution gap based on privacy-preserving. A Gini coefficient measurement system of income distribution gap based on privacy-preserving is established which includes cloud server CS, client CR, trusted third-party institution TI, and scientific research institution SRI. Firstly, the Paillier homomorphic encryption algorithm is applied in the scheme to encrypt the client’s private data. When the cloud server receives the encrypted data from clients, the cloud server will calculate the ciphertext for calculating Gini Coefficient by aggregating and averaging the encrypted data and will send the ciphertext to the scientific research institution. Finally, the scientific research institution decrypts the ciphertext and calculates the Gini coefficient. Security analysis shows that the proposed scheme achieves integrity and can preserve all users' privacy. Meanwhile, performance analysis demonstrates that the scheme has efficient computing and communication performance for practical applications.