基于深度特征的IDS报警误报消除算法

Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition Pub Date : 2022-11-17 DOI:10.1145/3581807.3581890

Jie Cheng, Jingchu Wang, Ang Xia, Lu Teng, Jianyi Liu

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引用次数: 0

摘要

针对入侵检测系统原始告警日志数据中存在大量虚警的问题，提出了一种基于深度特征的虚警消除算法。该算法利用真实报警的相关特征提取六种深度特征，并将其输入到四层神经网络中，用于判断报警日志的真实性。实验表明，该方法能够快速有效地从大量的告警日志中过滤出虚警。

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Deep Features Based IDS Alarm False Positive Elimination Algorithm

Aiming at the problem that there are a lot of false alarms in the original alarm log data of IDS, a false alarm elimination algorithm based on deep features is proposed. The algorithm extracts six kinds of deep features by using the relevant features of real alarms, and inputs them into the four-layer neural network to judge the authenticity of alarm logs. The experiments show that this method can quickly and effectively filter out false alarms from a large number of alarm logs.

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Proceedings of the 2022 11th International Conference on Computing and Pattern Recognition

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