Design and Implement of Operational Rule Base Based on Machine Learning and Association Rule Mining

In order to ensure the security, stability and effective operation of information system, the construction and optimization techniques for information operational Rule Base has become an urgent problem to be solved. To meet the demands, this paper presents a rule base construction and optimization strategy based on machine learning and association rule mining. The operational rule base which includes basic rules, association rules and extension rules is generated by the network topology, the monitoring indicators and the association rule mining of historical data. Then implement machine learning method for rules to improve their performance. At last, the rule-upgrade strategy is proposed for rules to move from the lower region to higher region. Based on these steps, experimental results are given to verify the proposed strategy.