Research On The Usage Control System Based On Behaviour Trust In Internet Of Things

Access control mechanism of reliabity and security is a means to ensure the safety of network, which is a relatively active technology. It can effectively prevent the illegal users from entering the system and the legitimate ones from abusing the privilege so as to ensure a controlled and legal use of system resources, which is a hotspot of research on network security in recent years. Different from the access control technology of general network, the IoT (Internet of Things, IoT) does not rely on fixed infrastructure. Its’resource limitations and most nodes are suppoted by batteries determine this research is a challenging task. Compared with traditional networks, IoT is more vulnerable to various security threats and attacks, including passive eavesdropping, data tampering and retransmission, forged identity and denial of service, etc., the access control solution used in the traditional network cannot be applied in the IoT directly.On the basis of predecessors’research, this article designs the mechanism from the perspectives of nodes’behavior and usage control for providing new train of thought to guarantee the security of the IoT The main research content is summarized as follows:In this paper we propose a trust model based on grey theory. Since the trust value of nodes as input to the access control mechanism, its accuracy determines the stability and effectiveness of the latter. This model fully monitored the behaviors of nodes in network, builded sample matrix, and computed the weight of the recommending nodes by grey relational method, and computed nodes’trust value through the clustering algorithm of grey theory. Simulation experiments showed that compared with the classic RFSN model, the convergence of the trust value of nodes in IoT is more gentle, could resist malicious recommendation by reducing the value of untrusted nodes in a timely manner. Compared with the TCM-BE model based on Bayes estimation, even under the circumstances of less recommended samples, GTTM still could keep low rate of false positive malicious nodes.In this paper we propose a distributed usage control system based on cross-layer design, which study the behaviour of sensors in different network levels, and judge the trust domains to generate different usage control strategies by k-means clustring with parameters. This system can deliver cross-layer information reliably and save energy by dividing the trust domains offline. Experiments results show it can update permission dynamically in real time, and isolate usage of data with not trust sensors to ensure the reliable operation of the network.