Research on Remote Computer Fault Detection Based on Big Data Algorithm Model

The main function of intrusion detection technology is to discover the endless attack attempts, attacks and attack results, and to ensure the confidentiality, integrity and availability of system resources through technical means, and finally form a dynamic and effective protection strategy. The application of data mining (DM) makes the computer fault detection more efficient, which can detect the computer faults well and ensure the correct operation and use of the computer. Feature selection can well eliminate redundancy and noise features, which is beneficial to improve the detection speed and effect of Intrusion Detection System (IDS). This article presents a computer network intrusion detection model based on feature selection algorithm, and then realizes remote computer fault detection. The simulation results show that IDS constructed by the feature selection algorithm proposed in this article has better performance than IDS without feature selection in detection time, detection accuracy of known attacks and detection accuracy of unknown attacks.