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Research on audit log association rule mining based on improved Apriori algorithm

机译:基于改进Apriori算法的审计日志关联规则挖掘研究

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Aimed at solving the problem of low-level intelligence and low utilization of audit logs of the security audit system, a secure audit system based on association rule mining is proposed in this paper. The system is able to take full advantage of the existing audit logs, establish the behavior pattern database of users and the system with data mining technique, and discover abnormal situation in a timely manner, which improves the security of computer system. We propose an improved E-Apriori algorithm which narrows the scanning range of the transactions, lowers the time complexity, and refines the operating efficiency. Experiment results on the Weka platform indicate that our proposed E-Apriori algorithm clearly outperforms the traditional Apriori algorithm, especially in the large sparse datasets.
机译:针对安全审计系统的审计日志智能低,审计日志利用率低的问题,提出一种基于关联规则挖掘的安全审计系统。该系统能够充分利用现有的审计日志,利用数据挖掘技术建立用户和系统的行为模式数据库,及时发现异常情况,提高了计算机系统的安全性。我们提出了一种改进的E-Apriori算法,该算法缩小了交易的扫描范围,降低了时间复杂度,并提高了操作效率。在Weka平台上的实验结果表明,我们提出的E-Apriori算法明显优于传统Apriori算法,尤其是在大型稀疏数据集中。

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