- 期刊
Adaptive Access Control Model of Vehicular Network Big Data Based on XACML and Security Risk
摘要
With the constant expansion of vehiclescale and the continuous development of Internet of Vehicles, the network environment of the data resource of Internet of Vehicles is becoming more and more complex. Traditional access control models have been difficult to meet the requirements of various access control conditions and dynamic adaptive adjustment of access control strategy. Aimed at the problem of adaptive access control model of vehicular network big data environment, XACML powerful ability of expressing access strategy is used in the paper, and we conduct the risk quantification based on 10 counts of risk factors, risk threshold and risk quota mechanism are also used for risk management. Experimental verification indicated that the risk adaptive access control model is effective, the research results will have great significance for promoting the application research of Internet of Vehicles and its safety technology and improving people's quality of life.