面向复杂网络的异常检测研究进展
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(宁波大学信息科学与工程学院,浙江宁波315211)

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E-mail: dongyihong@nbu.edu.cn.

中图分类号:

TP391

基金项目:

浙江省自然科学基金项目(LY20F020009,LZ20F020001);国家自然科学基金项目(61602133);宁波市自然科学基金项目(202003N4086,2019A610093);宁波大学“海洋生物技术与海洋工程”学科群专项项目(422004582).


Research progress of anomaly detection for complex networks
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(Faculty Electrical Engineering and Computer Science,Ningbo University,Ningbo315211,China)

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    摘要:

    异常检测是指识别数据集中显著区别于其他正常模式的数据,广泛应用于欺诈检测、入侵检测、数据分析等领域.现有的异常检测研究大多是基于非结构化数据点集,而现实中数据间复杂的结构关系构成了复杂网络,在数学形式上表示为图,所以面向复杂网络的异常检测的需求日益增加.对此,总结了当前复杂网络异常检测的方法与研究进展:首先提出复杂网络异常检测的必要性与发展历史;其次,分别从静态图和动态图的视角将复杂网络异常检测分为基于结构、社区、关系学习的静态图异常检测和基于节点、边、子图、全图的动态图异常检测;然后,分类别地进行概述、分析与比较,并给出复杂网络异常检测的应用场景;最后,总结未来面向复杂网络异常检测的研究方向.

    Abstract:

    Anomaly detection is to identify data that is significantly different from other normal patterns in the data set, and is widely applied in fraud detection, intrusion detection, and data analysis and other fields. Existing researches on anomaly detection are mostly based on unstructured data point sets, and there are complex structural relationships between data to form a complex network in the real world, and the network is represented as a graph in mathematical form, so the demand of anomaly detection for complex networks is increasing. This paper summarizes the current methods and research advances of anomaly detection for complex networks. First, the necessity and development history of anomaly detection for complex networks are proposed. Then, from the perspective of static and dynamic graphs, the anomaly detection for complex networks is divided into static graph anomaly detection based on structure, community, relationship learning, and dynamic graph anomaly detection based on nodes, edges, subgraphs, and full graphs, and then summarize, analyze and compare by category, and the application scenarios of anomaly detection for complex networks are given. Finally, the future research directions of anomaly detection for complex networks are summarized.

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苏江军,董一鸿,颜铭江,等.面向复杂网络的异常检测研究进展[J].控制与决策,2021,36(6):1293-1310

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  • 在线发布日期: 2021-05-10
  • 出版日期: 2021-06-20