| 凌宝红,李彤,胡敏,胡东辉.基于同态加密和区块链的成绩分析方案[J].安徽建筑大学学报,2024,32(): |
| 基于同态加密和区块链的成绩分析方案 |
| Grade Analysis Based on Homomorphic Encryption and Blockchain |
| 投稿时间：2023-12-27 修订日期：2024-03-25 |
| DOI： |
| 中文关键词: 计算机应用技术 智慧教学 成绩分析 同态加密 区块链 隐私保护。 |
| 英文关键词: technology for computer applications smart teaching score analysis homomorphic encryption blockchain privacy protection |
| 基金项目:安徽省高等学校科研编制计划项目(2022AH053074)、安徽省职成教学会教育教学规划重点课题(AZCJ2023045)、安徽省高校质量工程项目（2021jxtd051)。 |
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| 摘要点击次数: 772 |
| 全文下载次数: 213 |
| 中文摘要: |
| 随着数字化时代的推进,智慧教学的成绩分析技术在引导学生学业发展、实现个性化教学以及课程改进与调整方面发挥着越来越关键的作用。然而,传统的明文形式成绩分析存在学生个人数据泄露的风险,给学生的学习积极性带来不利影响,从而背离了成绩分析技术提升学生学习能力的初衷。在本文中,我们提出了一种基于同态加密和区块链的成绩分析方案,并对其中的恶意行为进行了分析。通过BGN同态加密,在密文域中实现了具体排名和分析指标的精确计算,完全消除了学生和分数之间的直接映射,保护了成绩数据的安全性。该方案为教师调整教学方案提供了参考,并为学生学习计划提供了指导。在成绩分析功能正常运作的前提下,满足了不同学生和教师对隐私的需求,保障了学生成绩的隐私安全。此外,利用区块链存储分析过程中的数据,为后续方案调整也提供了佐证。安全性分析和实验结果表明,本文方案在保证成绩分析功能的同时,保护了数据隐私。 |
| 英文摘要: |
| With the advancement of the digital era, the technology of grade analysis schemes in smart education is playing an increasingly pivotal role in guiding students" academic development, implementing personalized teaching, and improving and adjusting courses. However, the plaintext in traditional grade analysis carries the potential risk of exposing students" personal data, consequently dampening their enthusiasm for learning. This impact contradicts the original purpose of grade analysis schemes to improve students" learning abilities. In this paper, we propose a grade analysis scheme based on homomorphic encryption and blockchain and analyze malicious behaviors within the scheme. Leveraging BGN homomorphic encryption, we achieve precise calculations of specific rankings and analysis indicators in the ciphertext domain, completely eliminating the direct mapping between students and their grades, thereby ensuring the security of grade data. The scheme provides teachers with references to adjust their teaching plans and offers guidance for students" learning plans. It addresses the privacy requirements of different students and teachers while ensuring the normal functioning of grade analysis, thus safeguarding the privacy of student grades. Moreover, we utilize blockchain technology to store data generated during the analysis process, serving as evidence for future scheme adjustments. Security analysis and experimental results show that the scheme in this paper protects data privacy while ensuring the grade analysis. |
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