使用递归量化分析识别OSPF异常
Identifying OSPF Anomalies Using Recurrence Quantification Analysis
摘要：
开放最短路径优先（OSPF）是管理域内路由的最广泛使用的路由协议之一。OSPF协议存在许多严重的安全问题。LSA伪造是导致路由环路和黑洞的最关键漏洞之一。网络运营商需要快速识别此类异常。网络运营商还需要识别硬件故障。在本文中，我们调查的能力，递归量化分析（RQA），一种先进的非线性统计分析技术，以确定OSPF异常。我们评估RQA的能力，以确定OSPF异常使用一个受控的测试平台，我们介绍了不同类型的LSA伪造以及硬件故障。我们的评估表明，RQA可以快速检测OSPF异常。
英文摘要：
Open Shortest Path First (OSPF) is one of the most widely used routing protocol to manage intra-domain routing. OSPF has been identified with many serious security issues. LSA falsification is one of the most critical vulnerability that can cause route loop and black hole. Network operators need to rapidly identity such anomalies. Network operators need also to identify hardware failure. In this paper, we investigate the capability of Recurrence Quantification Analysis (RQA), an advanced nonlinear statistical analysis technique, to identify OSPF anomalies. We evaluate the capability of RQA to identify OSPF anomalies using a controlled testbed where we introduced different types of LSA falsifications as well as hardware failures. Our evaluation shows that RQA can rapidly detect OSPF anomalies.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
