Research on Real-Time Network Security Risk Assessment and Forecast

Abstract

Modern security problems focus on sensibly allocating resources to decrease the magnitude of potential hazards, decrease the chances of adversary success given an attempt, or minimize loss following a successful attack. However, current risk assessment methodologies focus on manual risk analysis of network during design or through periodic reviews. Techniques for real-time risk assessment are scarce. In this paper, we propose a novel real-time risk assessment method using fuzzy logic and Petri Nets. The proposed method enables decision analysts to better understand the complete evaluation process of network security risk assessment, Furthermore, this approach can predict the potential network risk and provide credible confidence scores of risk assessment. The experimental results show that the proposed method is very useful in network security risk assessment.