基于确定性决策自动机的IPv6扩展头部威胁的自适应检测模型
Bin Lin1, Liancheng Zhang2, Hongtao Zhang3
1School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, 450001, China.
Scientific reports
|April 25, 2024
概括
本研究引入了针对IPv6扩展头部威胁 (ADM-DDA6) 的自适应检测模型,显著提高了安全性. ADM-DDA6提供更快的威胁检测和最小的性能影响,增强网络安全协议.
科学领域:
- 计算机科学 计算机科学
- 网络安全 网络安全
- 网络安全 网络安全
背景情况:
- IPv6扩展头提供灵活性,但引入安全漏洞,如防火墙规避.
- 目前的威胁检测方法缺乏普遍性,速度和全面的检测能力.
- 现有的解决方案难以应对复杂的威胁,例如头部失调和重复.
研究的目的:
- 为IPv6扩展头部威胁 (ADM-DDA6) 提出一个自适应检测模型.
- 为了提高检测各种IPv6扩展头部安全威胁的速度和准确性.
- 开发一个模型,尽量减少网络基础设施的性能开销.
主要方法:
- 为常见的IPv6扩展头设计了标准规则集,通过20条规则检测到70种威胁.
- 开发了一种方法来解析头部,匹配规则,建立过渡,并确定数据包威胁状态.
- 实施了自适应规则匹配技术,该技术基于标题类型动态选择规则集.
主要成果:
- 通过简洁的规则,成功检测了70种威胁类型.
- 适应模型展示了优越的检测速度,超过了Suricata和Snort.
- 即使威胁增加,ADM-DDA6的CPU开销最小 (0.7%),内存没有显著增加,即使威胁增加.
结论:
- ADM-DDA6有效地检测到常见和复杂的IPv6扩展头部威胁.
- 适应性方法显著提高了检测速度和效率.
- 该模型为保护IPv6网络提供了可扩展和高性能解决方案.
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