InSight2: An Interactive Web-Based Platform for Modeling and Analysis of Large-Scale Argus Network Flow Data
January 2018 • Presentation
Angel Kodituwakku (The University of Tennessee Knoxville), Dr. Jens Gregor (The University of Tennessee Knoxville), J.T. Liso (The University of Tennessee Knoxville)
In this presentation, the authors discuss InSight2, an interactive web-based platform for modeling and analysis of large scale argus network flow data.
University of Tennessee
Network monitoring systems are paramount to the proactive detection and mitigation of problems in computer networks related to performance and security. Degraded performance of network equipment and compromised end-nodes can cost computer networks downtime, data loss, and reputation. InSight2 is a web-based platform developed for the purpose of proactive and predictive monitoring of network performance and security aspects and providing intuitive visualizations thereof in organized dashboards in near real time. InSight2 models and analyzes network transactions to provide insight in to the network performance such as current bandwidth utilization, packet rate, packets dropped and the number of nodes online. InSight2 also uses up-to-date emerging threat lists and data analytics to identify denial of service attacks, botnets, ransomware servers, bogons, compromised hosts, spammers, scanners and a host of other types of malicious agents in the network. All data is automatically tagged with geographical, organizational, and other related information for identification and further investigation.