日志数据挖掘在入侵检测中的应用：基于支持向量机的模型研究

随着互联网的发展，信息安全问题日益凸显，入侵事件频繁发生。日志数据已成为信息安全的重要数据源，通过对日志数据的挖掘分析，可以有效发现并防范攻击事件。本文综述了当前日志数据挖掘技术的研究进展，包括日志数据预处理、特征提取、分类算法等方面。针对入侵检测任务，本文提出了基于支持向量机的入侵检测模型，并在公开数据集上进行了实验验证。结果表明，该模型能够有效识别入侵行为，具有一定的推广应用价值。

With the development of the Internet, information security issues have become increasingly prominent, and intrusion incidents occur frequently. Log data has become an important data source for information security. By mining and analyzing log data, attack events can be effectively detected and prevented. This article summarizes the research progress of current log data mining technology, including log data preprocessing, feature extraction, classification algorithms, etc. For intrusion detection tasks, this article proposes an intrusion detection model based on support vector machines and conducts experimental verification on public datasets. The results show that the model can effectively identify intrusion behaviors and has certain promotion and application value.