在以太坊中用于早期DDoS检测的预测方案的可视化
1Division of Computer Science, Sookmyung Women's University, Seoul 04310, Republic of Korea.
Sensors (Basel, Switzerland)
|December 23, 2023
概括
本研究介绍了一种新的区块链可视化方案,用于早期检测分布式拒绝服务 (DDoS) 攻击. 通过预测未来的系统状态,它可以主动缓解这些重大威胁.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 数据可视化 数据可视化
背景情况:
- 区块链技术提供了强大的数据保护,但很容易受到攻击.
- 分布式拒绝服务 (DDoS) 攻击对区块链系统构成重大威胁,导致交易处理失败.
- 现有的可视化方案缺乏早期检测能力,只显示过去和当前的数据.
研究的目的:
- 开发一种新的可视化方案,用于早期检测区块链系统上的DDoS攻击.
- 通过统计分析提高DDoS攻击检测的准确性.
- 赋予系统管理人员主动缓解策略的权力.
主要方法:
- 利用区块链数据上的多项式回归来预测未来的系统状态.
- 实施使用确定系数的统计分析方法,以提高检测准确度.
- 开发一种新的可视化方案,将预测的未来状态与历史数据一起显示.
主要成果:
- 拟议的可视化方案准确地预测了未来的区块链状态.
- 该系统以最小的预测错误有效预测DDoS攻击.
- 确定系数提高了拟议的检测方法的准确性.
结论:
- 这种新的可视化方案能够早期识别和缓解DDoS攻击.
- 预测未来的区块链状态对于主动安全管理至关重要.
- 这项研究为保护基于区块链的应用程序免受复杂威胁提供了有价值的工具.
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