Research On SSDF Detection Algorithm Based On Edge Computing For Oil And Gas IoT

By collecting data from production,storage and transportation terminal industrial equipment,Oil & Gas Io T realizes data monitoring and centralized management of equipment from oil and gas production to storage and transportation,providing a stable and reliable network environment for oil and gas industry to realize networking,digitalization and intelligence.However,the Io T cannot solve the problem of spectrum resource shortage caused by the increase of connected devices and cannot effectively defend against malicious attacks in the Io T,and its capability in security and reliability is insufficient.The oil and gas Io T based on Cognitive Radio technology combines Cognitive Radio technology with Io T,and collaboratively shares spectrum by using the dynamic spectrum allocation method in Cognitive Radio technology to access unauthorized Io T devices to the licensed spectrum band without interfering with Primary User,which effectively improves the spectrum utilization of Io T.This approach effectively improves the spectrum utilization of Io T.In contrast,cognitive radios are subject to Spectrum Sensing Data Falsification attacks from malicious Io T devices in the collaborative spectrum sensing process,which will tamper with local decision reports and affect the judgment of Fusion Center fusion center’s judgment,which will eventually lead to conflicting spectrum access and system disruption.In this paper,based on the National Science Foundation of China and the Natural Science Foundation of Heilongjiang Province,we conduct a theoretical and technical research on oil and gas Io T based on cognitive radio technology and provide an in-depth analysis on how to defend against spectrum-aware data forgery attacks in oil and gas Io T.(1)For independent attacks,a weighted fusion spectrum sensing strategy based on Hidden Markov Model is proposed in this paper.The method uses the Hidden Markov Model to detect the probability of malicious attacks at each node and reports to the fusion center,and the FC evaluates the submitted observations and assigns reasonable weight values to improve the accuracy of the sensing results.(2)For the collusion attacks,the BIRCH algorithm is used to divide the Io T devices in a region into several sub-clusters.The Io T devices in each sub-cluster only need to send the sensing reports to the sub FC they belong to,and the FP-growth algorithm is executed in the sub FC to identify the Collusive Malicious Io T Devices and filter their sensing reports,and finally only the sensing reports of normal Io T Devices will be Devices are sent to FC,which performs data fusion on the received perception reports and makes global decisions.