Metric forensics: a multi-level approach for mining volatile graphs

Advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. Existing graph analysis techniques are not appropriate for such data, especially in cases where streaming or near-real-time results are required. An example that has drawn significant research interest is the cyber-security domain, where internet communication traces are collected and real-time discovery of events, behaviors, patterns, and anomalies is desired. We propose METRICFORENSICS, a scalable framework for analysis of volatile graphs. METRICFORENSICS combines a multi-level “drill down” approach, a collection of user-selected graph metrics, and a collection of analysis techniques. At each successive level, more sophisticated metrics are computed and the graph is viewed at finer temporal resolutions. In this way, METRICFORENSICS scales to highly volatile graphs by only allocating resources for computationally expensive analysis when an inte...

• Type: Conference
• Year: 2010
• Where: KDD
• Authors: Keith Henderson, Tina Eliassi-Rad, Christos Faloutsos, Leman Akoglu, Lei Li, Koji Maruhashi, B. Aditya Prakash, Hanghang Tong
• Keywords: Data Mining, Graph Analysis Techniques, KDD 2010, Volatile Graph Data, Volatile Graphs