With the continuous expansion of cloud computing, the intrusion of civil aviation internal network and the abnormal behavior of internal users have become a new problem of cloud computing security. Aiming at the problem of intrusion detection and abnormal behavior analysis of internal network, this paper studies the intrusion detection data set by using the machine learning typical classified algorithm of Weka software, and realizes the malicious behavior of civil aviation internal network users through naive Bayesian algorithm, the behavior and normal behavior are classified and analyzed, and the naive Bayesian algorithm has high classified accuracy for abnormal behavior. It can effectively classify and mine the internal network user behavior of cloud computing intrusion detection data. Through experiments, the effectiveness of the proposed scheme and algorithm is verified.


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    Title :

    Research on Classification Algorithm for Civil Aviation Internal Network Intrusion Detection Based on Machine Learning


    Contributors:
    Yang, Hu (author)


    Publication date :

    2020-10-14


    Size :

    278768 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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