| As people pay more and more attention to personal privacy information,how to improve the protection of related privacy information in the medical environment has become one of the research hotspots.As the number of medical-related wearable devices increases with the development of the Internet of Things technology,a large amount of user-related medical privacy data is stored on these devices,such as user physiological information,activity trajectories,and sleep conditions.Data protection often uses access control methods.However,due to the resource-constrained environment characteristics of current embedded devices,the access control model cannot be fully implemented.Therefore,a lightweight access control method needs to be designed to solve this problem.On the other hand,due to the special nature of the medical environment,the complexity of access control is much higher than in other scenarios.Static access policies can no longer meet unexpected conditions in the medical environment,so the Break-Glass mechanism is usually used as an access control emergency Means of processing.However,the existing Break-Glass mechanism still has some disadvantages:malicious requests cannot be accurately identified,and when risky access behaviors occur,the system cannot reject these improper access requests.In view of the above problems,this article has two main tasks:one is to solve the shortcomings of the current Break-Glass mechanism,this paper implements a Break-Glass decision method based on complex networks in a medical environment,and the other is based on this decision method A lightweight access control model in a medical environment is proposed.The details are as follows:1.The Break-Glass decision method based on complex network proposed in this paper mainly includes two core algorithms,one is the correlation between symptoms and diseases:when an emergency occurs,the patient’s current symptom information can be used to calculate the possible cause of the symptom.Suspected disease occurred.The second is the correlation algorithm between diseases:on the premise of obtaining the suspected disease of the patient,the correlation between the patient’s historical disease and the suspected disease is obtained.The Break-Glass mechanism uses this correlation as a basis to make a decision to allow or deny access to the emergency request..The final result shows that the method is reasonable.The accuracy rate is 91%when the request result is allowed access and 81%is denied.2.The above-mentioned Break-Glass mechanism is used as the basis and combined with the characteristics of embedded access control.This paper proposes a lightweight access control model in a medical environment.Two types of access control are designed according to whether they are emergency requests Efficient and secure access control process.This model transfers complex calculations to the cloud service platform and reduces the computing pressure of embedded devices.The final model has the characteristics of high security,flexibility,and lightweight.This article studies the Break-Glass mechanism in the current medical environment,improves the calculation method of the Break-Glass mechanism,and judges the legitimacy of the request from more patient-related information.Sex.And realized a lightweight access control model for embedded devices.Thanks to the improved Break-Glass mechanism,it makes the handling of emergency situations more reasonable and improves the accessibility of patient privacy data in emergency situations And reduce the probability of risky visits.At the same time,it can adapt to the current situation that embedded devices save a lot of user privacy information.Because a newer method is used to resolve the access control exception handling mechanism in the current medical environment,it is difficult to judge whether the request is legitimate,so it will be instructive for related research in the future. |
