Software Engineering Institute

Network throughput and complexity are increasing due to the increasing number of devices and data-driven applications, especially at universities and Research and Education (R&E) Networks. In this talk we present InSight2, an open platform, intended to monitor and facilitate the development of network analytics for these large-scale networks. University and R&E networks are facing a deficiency in operational and security awareness. Real-time behavioral visibility and analysis of networks are crucial to detect problems, predict patterns and protect the data and critical assets. Conventional monitoring techniques and tools do not scale well in these environments. Novel analytics must be developed to understand traffic behavior and security issues, addressing the complexity and throughput of these networks. Network managers, operators and analysts face difficulty finding tools to analyze the amount of the data they collect. Researchers and educators encounter a barrier to entry to develop network analytics. These issues can be addressed by an open platform, that facilitates collaboration among the global community for the development and improvement of network analytics. We present two analytics modules. The predictive analytics module forecasts network utilization and enables the detection of unexpected behavior. The botnet detection module identifies botnet activity in network traffic. Results from its various deployments as well as benchmarks are also presented.