作者: S. Mathew , R. Giomundo , S. Upadhyaya , M. Sudit , A. Stotz
关键词:
摘要: In this paper, we present a method of handling the visualization hetereogeneous event traffic that is generated by intrusion detection sensors, log files and other sources on computer network from point view detecting multistage attack paths are importance. We perform aggregation correlation these events based their semantic content to generate Attack Tracks displayed analyst in real-time. Our tool, called Event Correlation for Cyber-Attack Recognition System (EC-CARS) enables distinguish separate an evolving thousands network. focus here presenting environment framework using ECCARS along with screenshots demonstrate its capabilities.