Zero Trust Secure Access Technology For The Internet Of Things

In recent years,with the rapid development of technologies such as embedded software,5G networks,and hardware devices,Io T products have been upgraded at an extremely fast pace.Cloud computing services have also become widely adopted information service models for individuals and enterprises.Due to the limited performance and storage space of Io T devices,complex calculations and long-term data retention are not feasible.Therefore,numerous cloud computing service providers(such as Alibaba Cloud and Huawei Cloud)have offered services for Io T devices and users,deploying the functions that require computing power on high-performance cloud servers and uploading local data of device to the cloud for easy viewing and management.However,due to the increasingly diverse network demands of cloud computing services,traditional access control strategies based on boundary security are no longer applicable to this scenario.Therefore,this thesis proposes an innovative security protection layout based on the background of Io T secure access to cloud computing services,combined with the current popular zero trust network architecture and machine learning models.Aim to design an access control model suitable for the Io T device and user security access to cloud computing service.The core work of the thesis includes:(1)Proposing an attack behavior detection model based on XGBoost algorithm and GRU neural network.In response to the vulnerability and control of Io T devices,machine learning algorithms are used to detect the attack behavior of the access subject for subsequent trust value calculation.(2)Designing a dynamic trust evaluation algorithm based on access subject behavior.This algorithm calculates access subject trust values based on behavior detection results,based on fuzzy hierarchical analysis,and introduces reward and punishment mechanisms,time decay factors,differentiated weights,and other means to make the calculation results more accurate.(3)Designing a zero-trust access control model for Io T(BD-ZTBAC).The model introduces the concept of zero-trust,using access subject behavior parameters as the basis for trust calculation.The acquisition of behavior parameters and trust value calculation use the behavior detection model and trust evaluation algorithm proposed in this thesis This overcomes the shortcomings of traditional access control models,such as poor flexibility,accuracy,lack of internal attack protection,and unsuitability for Io T scenarios,making access control decisions more reliable.(4)Overall evaluation of the model,verifying and evaluating the trust evaluation algorithm and BD-ZTBAC model through experiments,and comparing them with other algorithms and models,demonstrating the feasibility and effectiveness of the proposed algorithms and models in the IoT field.