摘要
协同跨平面会话中断攻击(CXPST)通过反复对多条目标关键链路实施低速率拒绝服务攻击(LDoS)造成域间路由系统的级联失效,从而导致互联网的崩溃。在攻击发生的初期,准确定位受攻击的关键链路并进行针对性防御可遏制级联失效的发生。现有定位方法研究主要基于单源假设,没有考虑多条目标链路同时失效对路径撤回的影响,定位准确度受限。针对上述问题,该文提出一种基于加权统计匹配得分的多失效链路定位方法(WSFS),以级联失效攻击目标链路选择策略作为推断基础,将撤销路径长度的倒数作为权重对评分进行加权。基于实际网络拓扑和有利点位置的级联失效攻击仿真实验结果表明,WSFS比目前最优方法平均准确率可提升5.45%。实验结果证明WSFS相比于其他定位方法更适合应对域间路由系统级联失效下的目标失效链路定位问题。
Coordinated Cross Plane Session Termination(CXPST)repeatedly implements Low rate Denial of Service(LDoS)attacks on multiple target critical links,causing the cascading failure of the inter-domain routing system and the collapse of the internet.In the early stages of an attack,accurately locating the critical link under attack and carrying out targeted defense can prevent the occurrence of cascading failures.The research on existing locating methods is mainly based on the single-source hypothesis,and does not consider the impact of simultaneous failure of multiple target links on path withdrawal,so the locating accuracy is limited.To solve the above problems,a locating method is proposed based on Weighted Statistical Fit Score(WSFS).Using the target link selection strategy of cascading failure attack as inferring basis,scores are weighted by the reciprocal of the length of the withdrawal paths.The simulation results based on the actual network topology and vantage point location show that WSFS can improve the average accuracy rate by 5.45%compared with the current optimal method.Experimental results prove that WSFS is more suitable for locating target failure links in inter-domain routing system cascading failure than other locating methods.
作者
曾子懿
邱菡
朱俊虎
王清贤
陈迪
ZENG Ziyi;QIU Han;ZHU Junhu;WANG Qingxian;CHEN Di(Information Engineering University,Zhengzhou 450001,China;National Digital Switching System Engineering&Technological Research Center,Zhengzhou 450001,China)
出处
《电子与信息学报》
EI
CSCD
北大核心
2020年第9期2134-2141,共8页
Journal of Electronics & Information Technology
基金
国家自然科学基金(61502528)。
关键词
多失效链路定位
域间路由系统
级联失效
路径长度加权
Multiple failure link location
Inter-domain routing system
Cascading failure
Path length weighting