基于节点通信行为时序的指控信息流挖掘算法

doi:10.11959/j.issn.1000-436x.2019176

Abstract

Abstract:

With the situation that the content of the communication between the nodes in the network is unknown,an instruction flow mining algorithm based on the communication sequence was proposed.Firstly,by modelling the relativity of the communication actions and proposing the node communication actions model,the background communication and instruction communication actions was modelled.Moreover,FlowMine algorithm was proposed to solve such models and the convergence of the algorithm was analyzed.The algorithm estimated parameters by sampling and iteration which obtained a near optimal solution.Finally,the validity of the approach was verified by synthetic data and empirical data analysis.Experiment results show the convergence and reliable performance of FlowMine algorithm.

Key words: data mining, complex network, temporal sequence of actions, information flow

CLC Number:

TP301

Yingzhuo XIANG,Zhengguo XU,Ling YOU. Instruction flow mining algorithm based on the temporal sequence of node communication actions[J]. Journal on Communications, 2019, 40(9): 51-60.

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References 23

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数据集	所有邮件数量/件	指控信息流邮件/件
安然邮件	3 636	215

Instruction flow mining algorithm based on the temporal sequence of node communication actions

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