Enhancing power communication network security: A comprehensive cyber risk visual analytics framework with real-time risk assessment

Risk assessment is an effective way to counter cyber-attacks on the power communication network. However, many existing methods are imbalanced and overlook the security state of the attack source, leading to inaccuracies. To address these shortcomings, this paper presents a cyber risk visual analytics framework that effectively combines cyber risk assessment with network alarm visual analytics. For the imbalanced assessment, we propose a weighted risk expectation that considers the security states of the attack sources as well as multiple significant attack factors. We introduce a new node centrality called directed weighted degree (DWDegree), which considers not only the heterogeneity of edge directions, but also the impact propagated from/to the non-adjacent reachable nodes. Combining weighted risk expectation (WRE) and DW-Degree centrality (DC), we present an improved risk assessment method (WRE-DC) for network nodes and perform real-time risk assessment using WRE-DC and sliding window technique. In addition, a novel visual analysis system based on the real-time WRE-DC results and network alarms has been developed to improve the analysis of complex network risks. The experimental results obtained from real network alarm data confirm the effectiveness of the proposed method in significantly improving the accuracy of network node risk assessment.