Design and development of detection system for suspected danger signal in large cloud computing network

The traditional detection system for suspected danger signal in the large cloud computing network gives an alarm to any suspected danger signal. The system is usually disturbed by the huge amounts of alarm actions,which affects on the detection of the true danger signal,and leads to the inaccurate detection results. The detection system for danger signal in large cloud computing networks was designed and developed,into which the segmentation approximate matching method of binary is introduced. The detailed structure of the detection system for suspected danger signal in large cloud computing network is offered. The signal detected by the suspected danger signal detection module is matched with the signal in danger signal library of the memory module in real time to determine whether the signal is the suspected danger signal. The alarm signal and the feature information of the suspected danger signal are emitted by the adaptive module. The real-time detection module for suspected danger signal is adjusted according to the feature data. The simulation experimental results show that the designed system has high detection precision and adaptability.