Application of improved association rule algorithm in Natural Resource Cloud
According to the"Overall Informatization Construction Plan of the Ministry of Natural Resources"issued by the Ministry of Natural Resources,there is a need to enhance security protection measures for the external network of natural resources.This includes further improving the protection and construction of security management centers,secure computing environments,secure communication networks,secure area boundaries,and enhancing capabilities related to trusted verification,data security,active defense,security detection,notification and early warning,and emergency response.A security protection system has been established in the Natural Resources Cloud to integrate network security resources and enhance network security situational awareness capabilities.This addresses issues such as decentralized management of security resources,weak network security defense capabilities,and challenges in tracking and tracing threat attacks by the Ministry of Natural Resources.The goal is to achieve agile attack prediction and fast backtracking.To improve the work efficiency of the security protection system,the association rule algorithm in its security component detection engine module is enhanced.The improved algorithm initially converts threat alarm data into a standard machine-processable format during the data collection stage.Secondly,in the matrix calculation phase,the MapReduce distributed computing framework is used to improve the processing efficiency of frequent itemsets.Finally,three measures were taken to improve the algorithm based on the Apriori algorithm,including locking the range of frequent k-term sets in a single scan,matrix vector inner product operation,and reducing the generation of redundant candidate sets.Following the algorithm improvement,it is encapsulated in the algorithm engine component of the Natural Resource Cloud detection engine module,further enhancing the security protection capability of the Natural Resources Department.Experimental simulations indicate that the improved algorithm enhances processing efficiency by over three times compared to the classic Apriori algorithm when dealing with multi-source datasets with the same capacity network security and under the same dimension of association rule matrix.Compared to the classic Apriori algorithm,this algorithm unifies the format of data elements through data preprocessing during the data collection stage,reduces processing time using the MapReduce processing framework,and the dataset has been reduced through distributed parallel processing architecture and cloud computing.Compared to the incremental mining algorithm,this algorithm further shortens the time to process frequent k-item sets through three improvement measures.Although the incremental mining algorithm adopts the MapReduce processing framework,it frequently scans the global transaction matrix without optimizing the transaction matrix operation method.Its time complexity is still more than twice that of the algorithm proposed in this paper,which still leads to a high execution time of the algorithm.Therefore,the algorithm proposed in this paper demonstrates superior processing performance.In conclusion,the application of improved algorithms has achieved a new situation in the network security protection work of the Ministry of Natural Resources,transitioning from the traditional"passive attack"to"active defense".
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