| Abstract:When cloud platform data is attacked, the intruder can forge the network address or hide the real address through indirect attacks. At this time, the administrator not only needs to fix the loopholes, but also obtain evidence clues and traceability. For this reason, a real-time monitoring method for the location of intruders under the cloud platform is proposed. Analyze the design requirements of the cloud platform intrusion monitoring system and establish an intrusion monitoring model; set up the structure of the intruder location monitoring system from the aspects of data sources and security alarms, comprehensively consider various interference factors, design system circuits and software programs; use particle swarm multi-layer analysis The method is to determine the weight coefficient matrix of the intrusion characteristics, extract the behavior characteristics of the intruder, and estimate the possible path in advance; collect trace data through spectrum characteristics, and use these data to calculate the feature fuzzy clustering probability of the location to be monitored and trace information, which exceeds The data that sets the threshold is the location information of the intruder, realizing real-time monitoring. The simulation results show that the position information monitored by this method is highly consistent with the actual position, and the monitoring delay is low. |
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