Monitoring often requires insight into the monitored system as well as concrete specifications of expected behavior. More and more systems, however, provide information about their inner procedures by emitting provenance information in a W3C-standardized graph format. In this work, we present an approach to monitor such provenance data for anomalous behavior by performing spectral graph analysis on slices of the constructed provenance graph and by comparing the characteristics of each slice with those of a sliding window over recently seen slices. We argue that this approach not only simplifies the monitoring of heterogeneous distributed systems, but also enables applying a host of well-studied techniques to monitor such systems.
翻译:监测往往需要深入了解监测的系统以及预期行为的具体规格。然而,越来越多的系统通过以W3C标准图表格式发布出处信息,提供关于其内部程序的信息。在这项工作中,我们提出一种方法,通过对构建出处图的片段进行光谱图分析,并通过将每个切片的特征与最近看到的切片上滑动窗口的特征进行比较,来监测异常行为的出处数据。 我们争辩说,这种方法不仅简化了对多种分布系统的监测,而且能够应用一系列经过良好研究的技术来监测这些系统。