Treffer: Optimizing security for software deployed on cloud environment using evolutionary search ; تحسين أمن البرمجيات التي تعمل في البيئة السحابية باستخدام الخوارزميات الجينية

This research studies heuristic search-based optimization of service compositions. We have investigated applying Genetic Algorithms (GA) to optimize service-oriented architectures in terms of security goals and cost. Service composition security risk is measured by implementing the aggregation rules from the local security risk values of the aggregated services in the composition. We adapt the DREAD model for Security risk assessment by suggesting new categorizations for calculating DREAD factors based on a proposed service structure and service attributes. We implemented the YAFA-SOA Optimizer as an extension of an existing implementation of the GA to solve multi-objective optimization problems for varying number of objectives in the context of service oriented architectures. We conducted an experiment to investigate our Research Questions. The experiment results showed that applying multi-objective GA is feasible to find the optimized security and cost in Service oriented architectures. We were able to approve that adding security services to the generated composition reduces the risk severity of the generated composition and enhances its security in terms of confidentiality, integrity and availability (CIA).