After a composite service is deployed, user privacy requirements and trust levels of component services are subject to variation. When the changes occur, it is critical to preserve privacy information flow security. W...After a composite service is deployed, user privacy requirements and trust levels of component services are subject to variation. When the changes occur, it is critical to preserve privacy information flow security. We propose an approach to preserve privacy information flow security in composite service evolution. First, a privacy data item dependency analysis method based on a Petri net model is presented. Then the set of privacy data items collected by each component service is derived through a privacy data item dependency graph, and the security scope of each component service is calculated. Finally, the evolution operations that preserve privacy information flow security are defined. By applying these evolution operations, the re-verification process is avoided and the evolution efficiency is improved. To illustrate the effectiveness of our approach, a case study is presented. The experimental results indicate that our approach has high evolution efficiency and can greatly reduce the cost of evolution compared with re-verifying the entire composite service.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.61562087 and 61772270)the National High-Tech R&D Program(863)of China(No.2015AA015303)+2 种基金the Natural Science Foundation of Jiangsu Province,China(No.BK20130735)the Universities Natural Science Foundation of Jiangsu Province,China(No.13KJB520011)the Science Foundation of Nanjing Institute of Technology,China(No.YKJ201420)
文摘After a composite service is deployed, user privacy requirements and trust levels of component services are subject to variation. When the changes occur, it is critical to preserve privacy information flow security. We propose an approach to preserve privacy information flow security in composite service evolution. First, a privacy data item dependency analysis method based on a Petri net model is presented. Then the set of privacy data items collected by each component service is derived through a privacy data item dependency graph, and the security scope of each component service is calculated. Finally, the evolution operations that preserve privacy information flow security are defined. By applying these evolution operations, the re-verification process is avoided and the evolution efficiency is improved. To illustrate the effectiveness of our approach, a case study is presented. The experimental results indicate that our approach has high evolution efficiency and can greatly reduce the cost of evolution compared with re-verifying the entire composite service.
