Dynamic security metrics for measuring the effectiveness of moving target defense techniques

Moving Target Defense (MTD) utilizes granularity, flexibility and elasticity properties of emerging networking technologies in order to continuously change the attack surface. There are many different MTD techniques proposed in the past decade to thwart cyberattacks. Due to the diverse range of different MTD techniques, it is of paramount importance to assess and compare their effectiveness. However, each technique causes distinct (dynamic) changes in the network, making an objective comparison difficult. In this paper, we incorporate MTD techniques into a temporal graph-based graphical security model, and develop a new set of dynamic security metrics to assess and compare their effectiveness. To this end, we first categorize and compare different attack and defense efforts. Second, we describe the temporal graph-based graphical security model to capture dynamic changes made by various MTD techniques in the network. We then develop a new set of security metrics for attack and defense efforts to evaluate the effectiveness of the MTD techniques. We implement two different MTD techniques, namely network topology shuffle and software diversity, and show their effectiveness against a targeted attack scenario in our experimental analysis. The results demonstrate that the proposed dynamic security metrics can capture different properties of MTD techniques, permitting a more fine-grained comparison and offering guidance for selecting the most effective MTD technique