Research On Context-Aware Access Control And Its Application

With the rapid development of mobile smart device technology,a wide range of services can be provided for users to access and control resources remotely.As a result,more and more employees bring mobile smart devices to work and access company sensitive information frequently.However,mobile smart devices bring convenience to people's lives,but they also raise concerns about privacy issues and information security.Due to the mobility of mobile smart devices,traditional static security mechanism is not sufficient to solve the information security problems caused by mobile smart devices accessing sensitive resources anytime and anywhere.In the traditional access models such as the mandatory access control model,discretionary access control model,and role-based access control model are all based on authentication and give users related permissions.The static mechanism is not applicable to the dynamic access mode of mobile smart devices today.To solve this problem,this paper proposes a context-based dynamic access control model.Different from the traditional access control method,the scheme proposed in this paper takes the context information of the user into consideration when performing access control.For example,location information(GPS,Wi-Fi),voice,time and other context information.Therefore,how to identify the user's environmental conditions with high efficiency and high accuracy based on the user's context information,and to achieve secure and effective dynamic access control of mobile smart devices for context information has become a research hotspot.In response to the above issues,the main tasks of this paper include:(1)Location-based context-aware access control scheme,which utilizes Wi-Fi and GPS positioning ideas and machine learning technology to implement dynamic access control of users.Compared with similar schemes,it improves the accuracy of position detection and reduces the position context-aware time overhead.The security analysis shows that the scheme is secure and feasible.(2)Voice-based context-aware access control scheme,this scheme obtains the user's voice information when accessing the resource and analyzes it using the machine learning classification method.It realizes the dynamic identification of the user's access environment security,and then dynamically adjusts the user access permissions.(3)Through experimental simulation,the position detection accuracy,sound detection accuracy,and perception efficiency of the scheme are analyzed.The location context perception method proposed in this paper improves the accuracy and efficiency of the detection,and the sound context perception method used improves the recognition accuracy.Finally,compared with similar schemes,it shows that the scheme of this paper has a certain improvement in precision and efficiency.