Anti‐Leakage Method of Sensitive Information of Network Documents Based on Differential Privacy Model
Year: 2024
Type: article
Abstract: ABSTRACT This article proposes a method for preventing sensitive information leakage in network documents based on differential privacy models to ensure the security of sensitive information in network documents. Based on the definition of differential privacy and its Laplace mechanism, a differential privacy model was constructed to prevent sensitive information leakage in network documents. Using differential privacy based Laplace mechanism to protect the sensitive information dataset of network documents, and inputting the sensitive information dataset of network documents into the differential privacy model, the sensitive information in network documents is generalized and perturbed, and Laplace noise is added after transformation and compression to prevent leakage. Using roulette wheel sampling technology to sample and sort the original histograms of sensitive data in network documents, using a hierarchical partitioning algorithm to group the sorted histograms, and adding Laplace noise to the groups based on differential confidentiality Laplace mechanism to achieve leak prevention when publishing sensitive messages in network documents. The experimental results show that this method can ensure the security of sensitive information data in network documents and prevent sensitive information leakage in network documents. There is no data loss during the data conversion and compression process of sensitive information. At the same time, the protection effect of sensitive information is less affected by the amount of data, and the loss rate of sensitive information is lower.
Source: Security and Privacy
DOI: 10.1002/spy2.491
Authors: Shuhui Su, Yonghan Luo, Tao Li, Qi Chen, Juntao Liang
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4405760151