车联网大数据的安全访问控制模型设计

Design of Secure Access Control Model for Internet of Vehicles Big Data

本文设计了车联网大数据安全访问控制模型。通过数据感知层采集车联网数据,并利用数据加密标准算法实施加密处理。将加密后的数据通过网络通信层传输到安全访问控制中心,再通过安全认证模块赋予或限制用户访问权限。在异常数据监测模块中,应用孤立森林算法检测拥有访问权限的用户,并识别数据异常状况,将识别到的异常数据存储到异常监测存储数据库,安全访问终端以此为依据,拒绝或允许用户访问车联网大数据。实验结果表明,该模型能够有效识别车联网大数据中的异常数据,阻止不具备权限客户的访问操作,且安全访问控制通信与时间开销较低。

In the paper,a secure access control model for big data in the internet of vehicles is designed.The data of the internet of vehicles are collected through the data awareness layer and encrypted with the data encryption standard algorithm.The encrypted data is transmitted to the secure access control center through the network communication layer,and then users are granted or restricted access rights through the security authentication module.In the abnormal data monitoring module,the isolated forest algorithm is applied to detect users with access permission,identify abnormal data,and store the recognized abnormal data in the anomaly monitoring storage database.Based on this,the secure access terminal rejects or allows users to access the big data of the internet of vehicles.The experiment results show that the model can effectively identify abnormal data in the big data of the internet of vehicles,prevent the access operations of customers without access permission,and the communication and time cost of secure access control is low.