Research on Data Privacy Protection Mechanisms for Student Management Systems Based on Network and Information Security
Year: 2026
Type: conference-paper
Abstract: The deepening digital transformation in education has led to explosive growth in student management data, with security issues such as data breaches, misuse, and illegal transactions becoming increasingly prominent, posing serious threats to students 'legitimate rights and the stable operation of educational systems. Addressing the multi-source heterogeneity, high sensitivity, and full lifecycle complexity of student management data, this paper proposes a "five-layer, three-dimensional" privacy protection mechanism based on network and information security. Integrating core technologies including data anonymization, differential privacy, federated learning, and zero-trust access control, the mechanism provides comprehensive protection throughout the entire data lifecycle—from collection and storage to transmission, application, and destruction. Empirical deployment and performance testing in a university's student management system demonstrated that this approach reduces data leakage risks by 89.3% while maintaining data availability, with only a 12.7% increase in system response time—significantly outperforming traditional single-protection methods. The study concludes by identifying current challenges and future development directions, offering both theoretical insights and practical solutions for building robust data privacy protection frameworks in the education sector. The core novelty lies in the customized matching of diverse privacy technologies to each lifecycle tier under the proposed five-layer three-dimensional framework instead of simple technical superposition, which differentiates this work from existing studies that apply isolated security tools only for partial data protection.
Authors: Qinlong Sun, Xiangyu Liu, Hao Wu
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7202211633