一种基于区块链的深度学习方法,用于学生课程推和安全的数字认证
1Institute of Social Sciences, University of Mediterranean Karpasia, Mersin, Turkey.
Scientific reports
|August 9, 2025
概括
深度认证器-DX509模型通过提供个性化的课程建议和安全的证书发行,使用一种新的修改注意力启用深度长期短期记忆 (MA-DLSTM) 模型和X509区块链集成来改善电子学习.
科学领域:
- 教育技术的教育技术
- 计算机科学 计算机科学
- 网络安全 网络安全
背景情况:
- 电子学习和个性化学习需要强大的学生课程推和安全的证书发放系统.
- 现有的混合和协作过方法与课程更新,复杂性和证书安全性作斗争.
- 对提高学业成绩,个性化学习路径和安全认证的需求正在增长.
研究的目的:
- 引入Deep Certifier-DX509模型,解决当前学生课程推和证书发放系统的局限性.
- 提高电子学习环境中的课程建议和数字证书的安全性和准确性.
- 为个性化的学习旅程和可验证的学术资格提供安全有效的解决方案.
主要方法:
- 开发了深度认证器-DX509模型,集成了修改的注意力启用深度长期内存 (MA-DLSTM) 进行推.
- 整合了 X509 证书生成算法,利用 X509 区块链与工作证明 (PoW) 增强安全性.
- 在证书子系统内实施了两步身份验证过程,以提高安全性和数据完整性.
主要成果:
- 与现有技术相比,Deep Certifier-DX509模型表现出优越的性能.
- 实现了0.73.7的高真实用户率 (GUR).
- 展示的高效性能指标:内存使用量为453.81KB,交易时间为1.03s,响应速度为2.39s,吞吐量为119.52bps.
结论:
- 拟议的Deep Certifier-DX509模型有效地解决了课程更新,复杂性和电子学习建议和证书发行的安全性方面的挑战.
- 整合MA-DLSTM和X509区块链,为个性化的教育提供了一个安全,准确和高效的系统.
- 该模型在创建可靠和适应性的电子学习生态系统方面取得了重大进展.
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