一个基于地址空间森林的IPv6目标生成方法
Shunlong Hao1, Liancheng Zhang2,3, Hongtao Zhang4
1School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, 450001, China.
Scientific reports
|April 22, 2025
概括
一种新的IPv6目标生成方法6Probe使用IPv6地址空间森林 (6ASForest) 来显著增加扫描的活跃IPv6地址的数量. 这种方法克服了现有算法的局限性,使IPv6网络资产发现更有效.
科学领域:
- 计算机网络 计算机网络.
- 网络安全 网络安全
- 网络扫描 网络扫描
背景情况:
- 目前的IPv6目标生成算法仅限于低维模式,限制了IPv6网络资产的高效扫描.
- 现有的方法面临着种子地址分布不均,集群不可逆性,大规模损失和高维模式空间的挑战,阻碍了可扩展性和可检测性.
研究的目的:
- 提出一种新的IPv6目标生成方法,6Probe,可以克服现有算法的局限性.
- 提高互联网范围内的IPv6网络资产扫描的规模和效率.
- 改进高维模式和损失空间的探索,以更好地发现IPv6地址.
主要方法:
- 开发了6Probe,这是一个基于IPv6地址空间森林 (6ASForest) 的IPv6目标生成方法.
- 构建了多个IPv6地址空间树 (6ASTrees) 来形成6ASForest.
- 杆种子地址结构用于探索高维空间中的高活动区域.
主要成果:
- 与现有的算法相比,6Probe显著扩大了探测到的IPv6活跃地址的规模.
- 在平衡的种子集上,6Probe探测了2.6-4.81倍多的活跃地址,并产生了5.47-20.01倍多的低维节点,而不是5个典型的算法.
- 在不平衡的种子集上,6Probe探测了137.87%-492.74%的活跃地址,并产生了比HMap6.6更多的430.81%-712.80%的低维节点.
结论:
- 拟议的基于6ASForest的6Probe方法在IPv6目标生成效率和可扩展性方面提供了实质性的改进.
- 6Probe有效地解决了先前方法中低维模式和种子地址分布的局限性.
- 这种技术可以更全面,更有效地扫描IPv6网络资产,这对于整个互联网的安全和管理至关重要.
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