.png){kind=icon}
返回
A fast instance reduction algorithm for intrusion detection scenarios
.png){kind=icon}
OA
AI
DOI：10.1016/j.compeleceng.2022.107963.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We live in a world that is being driven by data. This leads to challenges of extracting and analyzing knowledge from large volumes of data. An example of such a challenge is intrusion detection. Intrusion detection data sets are characterized by huge volumes, which affects the learning of the classifier. So there is a need to reduce the size of the training sets. Fortunately, inspection and analysis of available intrusion detection data sets showed that many instances are very similar and do not provide relevant information to the classification process. This prompted to look for possibilities to use a fast algorithm that, as much as possible, removes similar instances in intrusion detection data sets while enforcing the detection rate. In this work, a new fast instance reduction algorithm is presented. The proposed algorithm provides greater efficiency during the training stage, without significantly affecting the efficacy during the intrusion detection task.
Keyword:
Instance selection
Data reduction
Intrusion detection
Data preprocessing
Data mining
Supervised classification
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.9
论文数:
6.7K
被引数:
1.3W
机构
引用论文
Effects of Integrase Strand Transfer Inhibitors (INSTIs) Versus Non-INSTI Regimen Exposures on Pregnancy Outcomes, Maternal Weight Gain and HIV Viral Suppression整合酶链转移抑制剂（INSTIs）与非INSTI方案暴露对妊娠结局、母体体重增加和HIV病毒抑制的影响
PREAI
分享收藏Dissimilar Properties of Vaccenic Versus Elaidic Acid in β‐Oxidation Activities and Gene Regulation in Rat Liver Cells.png)
Lipids
LipidsIF0
PREAI
分享收藏A data reduction strategy and its application on scan and backscatter detection using rule-based classifiers基于规则分类器的数据约简策略及其在扫描和反向散射检测中的应用OAAI
OAAI分享收藏
查看更多内容