CN113537321B - 一种基于孤立森林和x均值的网络流量异常检测方法 - Google Patents
一种基于孤立森林和x均值的网络流量异常检测方法 Download PDFInfo
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数据集名称 | 样本数量 | 数据维度 | 异常值数量 |
Shuttle | 49097 | 9 | 3437 |
Mulcross | 262144 | 4 | 26214 |
Satellite | 6435 | 36 | 2036 |
BreastW | 683 | 9 | 239 |
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CN113837325B (zh) * | 2021-11-25 | 2022-03-01 | 上海观安信息技术股份有限公司 | 基于无监督算法的用户异常检测方法及装置 |
CN117113235B (zh) * | 2023-10-20 | 2024-01-26 | 深圳市互盟科技股份有限公司 | 一种云计算数据中心能耗优化方法及系统 |
CN117336210B (zh) * | 2023-12-01 | 2024-04-16 | 河北九宸科技有限公司 | 物联网卡流量异常检测方法、装置、设备及存储介质 |
CN117978543B (zh) * | 2024-03-28 | 2024-06-04 | 贵州华谊联盛科技有限公司 | 基于态势感知的网络安全预警方法及系统 |
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CN108777873A (zh) * | 2018-06-04 | 2018-11-09 | 江南大学 | 基于加权混合孤立森林的无线传感网络异常数据检测方法 |
CN110505179A (zh) * | 2018-05-17 | 2019-11-26 | 中国科学院声学研究所 | 一种网络异常流量的检测方法及系统 |
CN110995508A (zh) * | 2019-12-23 | 2020-04-10 | 中国人民解放军国防科技大学 | 基于kpi突变的自适应无监督在线网络异常检测方法 |
CN112905583A (zh) * | 2021-04-01 | 2021-06-04 | 辽宁工程技术大学 | 一种高维大数据离群点检测方法 |
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US11582249B2 (en) * | 2019-11-27 | 2023-02-14 | Telefonaktiebolaget Lm Ericsson (Publ) | Computer-implemented method and arrangement for classifying anomalies |
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CN108777873A (zh) * | 2018-06-04 | 2018-11-09 | 江南大学 | 基于加权混合孤立森林的无线传感网络异常数据检测方法 |
CN110995508A (zh) * | 2019-12-23 | 2020-04-10 | 中国人民解放军国防科技大学 | 基于kpi突变的自适应无监督在线网络异常检测方法 |
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An improved X-means and isolation forest based methodology for network traffic anomaly detection;Yifan Feng 等;《PLOS ONE》;1-18 * |
An Optimized Computational Framework for Isolation Forest;Zhen Liu 等;《Mathematical Problems in Engineering》;1-14 * |
Research on the Model of Anomaly Detection of FMCG Based on Time Series;Qiaohong Zu 等;《Human Centered Computing》;293-303 * |
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