Study on the Mechanism for Guaranteeing the Right to Automated Processing of Personal Information in Environmental Governance

Abstract

Aiming at the privacy risk brought by the automated processing of personal information in environmental governance, this paper proposes a set of systematic rights protection mechanisms. Firstly, the kernel principal component analysis method is used to reduce the dimensionality of information attributes by reducing the dimensionality and noise reduction of personal information. Then based on the privacy protection technique of stream cipher, the peak density clustering (CFSFDP) algorithm is introduced to improve the k -TBM anonymization algorithm, and a privacy protection method based on the k-TBM anonymization model of CFSFDP (CFSFDP-k-TBM) is designed. Finally, this paper conducts experimental tests on the CFSFDP-k-TBM algorithm, and compares and analyzes it. The test results show that CFSFDP-k-TBM algorithm has more effective privacy protection effect while ensuring users' personalized privacy needs. Therefore CFSFDP-k-TBM based anonymization model is an applicable privacy protection method for personal information in environmental governance.