结合路由和流量数据,检测IP转发异常

M. Roughan, T. Griffin, Z. Morley Mao, A. Greenberg, Brian Freeman
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引用次数: 56

摘要

由于设备故障、实现错误、配置错误等原因导致的IP转发异常,会严重影响网络业务的正常运行。对此类异常进行稳健可靠的检测对于快速诊断问题、缓解问题和修复至关重要。我们提出了一种简单,鲁棒的方法,集成路由和流量数据流,以可靠地检测转发异常。整个方法是可扩展的、自动化的和自我训练的。我们发现这种技术有效地识别转发异常,同时避免了如果任何一个流被单方面使用而导致的高误报率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combining routing and traffic data for detection of IP forwarding anomalies
IP forwarding anomalies, triggered by equipment failures, implementation bugs, or configuration errors, can significantly disrupt and degrade network service. Robust and reliable detection of such anomalies is essential to rapid problem diagnosis, problem mitigation, and repair. We propose a simple, robust method that integrates routing and traffic data streams to reliably detect forwarding anomalies. The overall method is scalable, automated and self-training. We find this technique effectively identifies forwarding anomalies, while avoiding the high false alarms rate that would otherwise result if either stream were used unilaterally.
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