Security risk situation quantification method based on threat prediction for multimedia communication network

TL;DR: This work proposes a novel method for threat identification, and further builds a quantitative security risk model with it, which enables a manager to quantify the risks of any identified threat or ongoing attack and to recognize the vulnerable multimedia devices to keep secure multimedia communication.

Abstract: Multimedia communication network has gained remarkable popularity by a wide spectrum of users nowadays. It is easier that the potential threats conceal within the large-scale net flow of multimedia communication traffic. Once vulnerability exploitation occurs, the latent risk will be brought to the surface, causing a series of safety problems. Thus, the vulnerability analysis and threat prediction are becoming critical issues. Recently years, many investigations have been made. However, they are not sufficient. To provide a comprehensive view of the threat scenario and present a quantitative risk-aware approach, we propose a novel method for threat identification, and further we build a quantitative security risk model with it. Actually, two algorithms are proposed, namely dynamic Bayesian attack graph based threat prediction algorithm, and threat prediction based security risk quantification algorithm. The first algorithm aims to provide full prediction information with threat scenario. The second algorithm quantifies the threat in the first algorithm into the security risk from two levels: host and network. The examples indicate that our method is feasible and scalable, which enables a manager to quantify the risks of any identified threat or ongoing attack and to recognize the vulnerable multimedia devices to keep secure multimedia communication.