Despite the robust structure of the Internet, it is still susceptible to disruptive routing updates that prevent network traffic from reaching its destination. Our research shows that BGP announcements that are associated with disruptive updates tend to occur in groups of relatively high frequency, followed by periods of infrequent activity. We hypothesize that we may use these bursty characteristics to detect anomalous routing incidents. In this work, we use manually verified ground truth metadata and volume of announcements as a baseline measure, and propose a burstiness measure that detects prior anomalous incidents with high recall and better precision than the volume baseline. We quantify the burstiness of inter-arrival times around the date and times of four large-scale incidents: the Indosat hijacking event in April 2014, the Telecom Malaysia leak in June 2015, the Bharti Airtel Ltd. hijack in November 2015, and the MainOne leak in November 2018; and three smaller scale incidents that led to traffic interception: the Belarusian traffic direction in February 2013, the Icelandic traffic direction in July 2013, and the Russian telecom that hijacked financial services in April 2017. Our method leverages the burstiness of disruptive update messages to detect these incidents. We describe limitations, open challenges, and how this method can be used for routing anomaly detection.
翻译:尽管互联网的结构很健全,但它仍然容易受到干扰性路由更新,从而阻止网络流量到达其目的地。我们的研究表明,与干扰性更新相关的BGP公告往往发生在相对高频率的群体中,随后是不经常活动的时期。我们假设我们可能使用这些突发特征来探测异常的路由事件。在这项工作中,我们使用人工核实的地面真相元数据和公告数量作为基线措施,并提出一种突发性措施,以高回回调和准确度高于数量基线的方式探测先前异常事件。我们量化了四大事件日期和时间前后的跨抵达时间的突发性:2014年4月的Indosat劫持事件、2015年6月马来西亚电信泄漏、2015年11月的Bharti Airtel有限公司劫机和2018年11月的主要一号泄漏;以及导致拦截交通的三大规模较小的事件:2013年2月白俄罗斯交通方向、2013年7月的冰岛交通方向以及2017年4月劫持金融服务的俄罗斯电信。我们的方法可以利用干扰性更新信息来探测这些事件。我们描述了各种限制,我们使用的方法是公开的挑战。