Security-aware optimization for ubiquitous computing systems with SEAT graph approach

For ubiquitous computing systems, security has become a new metric that designers should consider throughout the design process, along with other metrics such as performance and energy consumption. A combination of selected cryptographic algorithms for required security services forms a security strategy for the application. In this paper, we propose methods to generate security strategies to achieve the maximal overall security strength while meeting the real-time constraint. In order to express security requirements of an application, we propose a novel graph model called Security-Aware Task (SEAT) graph model to represent real-time constraints and precedence relationships among tasks. Based on the SEAT graph approach, we propose an optimal algorithm, Integer Linear Programming Security Optimization (ILP-SOP). For the special structures such as simple path graph and tree, we propose two dynamic programming based algorithms (DPSOP-path/tree) to generate the optimal security strategy. Experiment results demonstrate the correctness and efficiency of our proposed method. The experimental results show that, by using our proposed techniques, the security strength can be improved by 44.3% on average. Highlights Propose a novel graph model SEAT that can express security requirements of each task. Use the security probability to measure security strength of a cryptographic algorithm. Optimal strategy achieved by our ILP while guaranteeing the system schedulability Two dynamic programming algorithms generate the optimal strategy in polynomial time.