计算机与现代化Issue(4)：1-8,8.DOI:10.3969/j.issn.1006-2475.2026.04.001
基于信息熵与风险厌恶视角的政府数据隐私计量与分级模型
Government Data Privacy Measurement and Classification Model Based on Information Entropy and Risk Aversion Perspective
摘要
Abstract
To address the limitations of traditional privacy measurement models in government data privacy protection,specifi-cally their neglect of data subjects'subjective preferences and insufficient cross-scenario robustness,this paper proposes a pri-vacy measurement and classification model based on information entropy and risk aversion.The model aims to achieve precise quantification of privacy risks and enhance the adaptability of classification strategies across different domains.By constructing a multi-level privacy element classification system,the model quantifies the inherent privacy information of data using information entropy theory.It further introduces a risk aversion mechanism for privacy leakage and designs a dynamic weight allocation strat-egy to respond to the core privacy needs of different departments.The model integrates regularization modules,privacy element measurement modules,and risk aversion calibration modules to collaboratively compute comprehensive privacy risk values.Ex-perimental results based on multi-source heterogeneous synthetic datasets demonstrate that the model significantly outperforms existing methods in terms of privacy measurement accuracy,privacy element sensitivity,and cross-scenario adaptability.The findings indicate that the synergy between information entropy and dynamic risk aversion weights enables multi-dimensional pre-cise assessment of privacy risks,providing a scientific basis for differentiated privacy protection in government data sharing and openness.关键词
政府数据/隐私安全/信息熵/风险厌恶/隐私计量Key words
government data/privacy security/information entropy/risk aversion/privacy measurement分类
信息技术与安全科学引用本文复制引用
俞瑛,马静..基于信息熵与风险厌恶视角的政府数据隐私计量与分级模型[J].计算机与现代化,2026,(4):1-8,8.基金项目
国家自然科学基金面上项目(72174086) （72174086）
浙江省高等教育学会专项重点课题(KT2024436) （KT2024436）
绍兴市哲学社会科学规划重点课题(145499) （145499）
浙江理工大学科技与艺术学院科研项目(KY2024002) （KY2024002）
