Research on Information Forensics Scheme Based on node2vec Neural Network

doi:10.3969/j.issn.1671-1122.2018.10.004

Abstract

Abstract:

Through the analysis of social information network (SIN), it is an important research direction of social cluster network to obtain the interpersonal relationship and community structure of specific goals in the real world. The research is of great significance in the field of criminal investigation and justice, which enables the investigators to describe the internal structure of criminal organization without physical capture/surveillance, and then to find the core members of criminal organization. Based on the relevant research in the field of forensics and some algorithms of machine learning neural network, this paper proposes a network forensics tool Vec2Rank-CrimeNet, and gives its effect in solving practical problems by taking the real crime data as experimental data.

Key words: social information network, criminal network, restructure, node2vec

CLC Number:

TP309

Xiangjiu CHE, Tianyue HU. Research on Information Forensics Scheme Based on node2vec Neural Network[J]. Netinfo Security, 2018, 18(10): 24-30.

Figures/Tables 4

References 19

[1]	HUANG Liwei, LI Deyi, MA Yutao, et al.A Meta Path-based Link Prediction Model for Heterogeneous Information Networks[J]. Chinese Journal of Computers,2014(4):848-858.
	黄立威, 李德毅, 马于涛,等. 一种基于元路径的异质信息网络链路预测模型[J]. 计算机学报, 2014(4):848-858.
[2]	WU Xindong, LI Yadong, HU Donghui.Study on Social Network Forensics[J]. Journal of Software, 2014(12): 2877-2892.
	吴信东, 李亚东, 胡东辉. 社交网络取证初探[J]. 软件学报, 2014(12):2877-2892.
[3]	SARVARI H, ABOZINADAH E, MBAZIIRA A, et al.Constructing and Analyzing Criminal Networks[C]// IEEE. 2014 IEEE Security and Privacy Workshops, May 17-18, 2014, San Jose, CA, USA.NJ: IEEE, 2014:84-91.
[4]	HARTIGAN J A, WONG M A.Algorithm AS 136: A K-Means Clustering Algorithm[J]. Journal of the Royal Statistical Society, 1979, 28(1):100-108.
[5]	AGGARWAL C C, XIE Yan, Yu P S. Towards Community Detection in Locally Heterogeneous Networks[EB/OL]..
[6]	TAHA K, YOO P D.SIIMCO: A Forensic Investigation Tool for Identifying the Influential Members of a Criminal Organization[J]. IEEE Transactions on Information Forensics & Security, 2016, 11(4):811-822.
[7]	ABADI M, AGARWAL A, BARHAM P, et al. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems[EB/OL]. .
[8]	DUAN Dagao, XIE Yongheng, GAI Xinxin, et al.A Rumor Detection Model Based on Neural Network[J].Netinfo Security, 2017,17(9):134-137.
	段大高, 谢永恒, 盖新新,等. 基于神经网络的微博虚假消息识别模型[J]. 信息网络安全, 2017,17(9):134-137.
[9]	GOLDBERG Y, LEVY O. Word2vec Explained: Deriving Mikolov et al.'s Negative-sampling Word-embedding Method[EB/OL]. .
[10]	GROVER A, LESKOVEC J.Node2vec:Scalable Feature Learning for Networks[C]// ACM. The 22nd ACM Sigkdd International Conference on Knowledge Discovery & Data Mining, August 13 - 17, 2016 , San Francisco, California, USA .New York: ACM, 2016:855-864.
[11]	LIU Hao, CHEN Zhigang, ZHANG Lianming.A Task-based Access Control Model of Peer-to -Peer Network Based on Admission Degree[J].Netinfo Security, 2017,17(6):22-29.
	刘浩, 陈志刚, 张连明. P2P网络中基于准入度的任务访问控制模型[J]. 信息网络安全, 2017,17(6):22-29.
[12]	CATANESE S, FERRARA E, FIUMARA G. LogAnalysis: A Tool to Study Communities inside Social Networks[EB/OL]. .
[13]	WANG Heyong, CHANG C K, YANG H L, et al.Estimating the Relative Importance of Nodes in Social Networks (Preprint)[J]. Journal of Information Processing, 2013, 21(3):414-422.
[14]	HU Yangrui, CHEN Xingshu, WANG Junfeng, et al.Anomalous Traffic Detection Based on Traffic Behavior Characteristics[J]. Netinfo Security, 2016,16(11):45-51.
	胡洋瑞, 陈兴蜀, 王俊峰,等. 基于流量行为特征的异常流量检测[J]. 信息网络安全, 2016,16(11):45-51.
[15]	GUO Xiaohe, LIU Ke, LIAO Huanwen.Enron Executives Organization Structure's Found Based on Complex Network[J].Journal of Nanchang Hangkong University, 2013, 27(3):103-108.
	郭小和, 刘科, 廖焕文,等. 基于复杂网络的安然公司高管组织结构发现[J]. 南昌航空大学学报, 2013, 27(3):103-108.
[16]	FERRARA E, MEO P D, CATANESE S, et al.Detecting Criminal Organizations in Mobile Phone Networks[J]. Expert Systems with Applications, 2014, 41(13):5733-5750.
[17]	XU J J, CHEN H.CrimeNet Explorer: a Framework for Criminal Network Knowledge Discovery[J]. ACM Transactions on Information Systems, 2005, 23(2):201-226.
[18]	NEWMAN M E. Fast Algorithm for Detecting Community Structure in Networks[EB/OL]. .
[19]	GIRVAN M, NEWMAN M E J. Community Structure in Social and Biological Networks[J].Proceedings of the National Academy of Sciences of the United States of America,2002(12):7821-7826.