计算机科学 ›› 2025, Vol. 52 ›› Issue (3): 391-399.doi: 10.11896/jsjkx.240100151
隋嘉祺1, 扈红超1,2, 史鑫2, 周大成2, 陈尚煜2
SUI Jiaqi1, HU Hongchao1,2, SHI Xin2, ZHOU Dacheng2, CHEN Shangyu2
摘要: 由于Tor低门槛的搭建条件和开放的参与机制,攻击者可以通过控制大量的恶意Sybil节点对Tor网络发起Sybil攻击,从而对用户隐私造成严重的威胁。目前,针对Sybil攻击的防御方法中,一类通过识别恶意Sybil节点来进行防御,该类方法存在对节点之间相似性分析缺乏准确性、难以识别恶意节点针对性伪装等问题;另一类通过提升Tor路径选择算法的安全性来进行防御,该类方法存在路径选择算法难以同时满足安全性和性能的双重要求、不能抵御多种Sybil攻击等问题。为了弥补现有防御方法自身存在的脆弱性问题,提出将恶意节点识别方法和路径选择算法综合应用。首先,从多个数据源采集中继节点的信息,并对多源数据进行验证、过滤和融合,提升数据层面的安全性;其次,通过基于历史数据的带宽度量优化,一定程度上增大了对带宽长期稳定的可靠节点的选择倾向,增加了攻击者部署恶意Sybil节点的成本;然后,优化中继节点相似性评估方法,提出一种基于聚合相似性得分的最近邻排序算法,提高节点相似性分析的准确性;最后,将优化后的相似性评估方法融入路径选择算法的设计中,提出一种基于相似性感知的路径选择算法。实验结果表明,该算法不仅在抵御多种Sybil攻击时表现出更好的防御效果,而且确保了链路的性能需求得到满足。
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