| Title | Enforcing Optimal Moving Target Defense Policies |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Zheng, Jianjun, Siami Namin, Akbar |
| Conference Name | 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) |
| Keywords | Analytical models, Bellman optimality equation, Computer science, control theory, decision making, Games, Iterative methods, Markov Decision, Markov Decision Process, Markov processes, Mathematical model, MDP model, Metrics, moving target defense, optimal moving target defense policies, optimal policy selection, optimal security policies, pubcrawl, resilience, Resiliency, Scalability, security, value iteration |
| Abstract | This paper introduces an approach based on control theory to model, analyze and select optimal security policies for Moving Target Defense (MTD) deployment strategies. A Markov Decision Process (MDP) scheme is presented to model states of the system from attacking point of view. The employed value iteration method is based on the Bellman optimality equation for optimal policy selection for each state defined in the system. The model is then utilized to analyze the impact of various costs on the optimal policy. The MDP model is then applied to two case studies to evaluate the performance of the model. |
| DOI | 10.1109/COMPSAC.2019.00112 |
| Citation Key | zheng_enforcing_2019 |
Enforcing Optimal Moving Target Defense Policies