The performance of the models is evaluated by several experiments with a popular NSL-KDD dataset. From the experimental results, we find the FNN and CNN models not only have a strong modeling ability for network anomaly detection, but also have high accuracy. Compared with several traditional ...
论文链接:[2106.06947v1] Graph Neural Network-Based Anomaly Detection in Multivariate Time Series (arxiv.org)主要内容论文提出了一种图偏差网络(GDN)框架用于多元时间序列异常检测,该框架可以实验对一个…
Introduction to the Dataset The Maple-IDS dataset is a network intrusion detection evaluation dataset designed to enhance the performance and reliability of anomaly-based Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS). As cyber attacks become increasingly sophisticated, having a...
The Maple-IDS dataset is a network intrusion detection evaluation dataset designed to enhance the performance and reliability of anomaly-based Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS). As cyber attacks become increasingly sophisticated, having a reliable and up-to-date d...
Such an analysis has been carried out taking into consideration different traffic features. The experimental results, obtained testing our systems over the publicly available MAWILAb dataset, point out that both the applied method and the chosen descriptor strongly impact the detection performance....
“Anomaly detection module and dataset” section introduces the whole anomaly detection module, experience dataset and pre-processing. “The DPC-GS-MND clustering algorithm” section presents the proposed DPC-GS-MND clustering algorithm and all technical points. “Evaluation” section implements complete ...
clean baseline:在ISCX dataset提取中第一天的数据以及一半的无攻击行为的数据,从而进行训练。预测得到异常流量。 dirty baseline:在完整的ISCX数据集上训练网络,使得模型可以学习攻击流量和非攻击流量。一旦学习了网络流量模型,然后使用该模型来预测数据集中每个流量的值。
The algorithm redefines the outlier degree and uses the neighborhood entropy as a new tool to measure the outlier degree,to improve the detection accuracy and noise immunity of the algorithm. Experimental results based on KDD Cup dataset show that the TCM-RNE improves the False Positive( FP) ...
We conducted experiments on the public training set NSL-KDD, which is considered as a modified dataset for the KDDCup 1999. The results show that our detection system has great precision in malicious traffic detection, and it achieves the effect of reducing the number of false alarms. 展开 ...
在四个数据集上进行了实验,超越了现有最佳方法,并提供了Synthetic Industrial Anomaly Dataset(SIA),方便用于自监督异常检测方法的研究。 方法创新点 提出了RealNet这一自监督异常检测框架,通过AFS和RRS两个组件实现了特征选择和重构残差的选择,提高了异常检测性能并减少了计算成本。 引入了SDAS这一新颖的合成策略,能够...