基于拓扑扩展的在线社交网络恶意信息源定位算法

doi:10.11896/j.issn.1002-137X.2019.05.020

Abstract

Abstract: Social media on the Internet has become the main interactive platform for online users with the rapid development of online social network.Malicious information often hides in the massive data of online social networks.In addition,the limitation of topologies and the disguise of malicious information bring a lot of difficulties for locating and tra-cing malicious information.On the one hand,it is difficult to achieve global monitoring by means of manual labeling.Evenby means of semantic analysis and information search,only the information “fragments” in the current network can be obtained after the hotspots are recognized.Coupled with the variation of information in the evolution process,a chain of propagation will be interrupted and split into multiple pieces.Without identifying and distinguishing,the number of information sources will be increased,and the algorithm complexity will be greatly increased.On the other hand,malicious information often uses camouflage techniques,such as providing false elements,manufacturing hotspots to attract users,and manipulating online “water army” to interfere with the public opinions,which makes the information topology and relation topology inconsistent.The original locating algorithm relies on the distribution of the current infected nodes and the current topology.The singularization of the infection state changes to randomization,making the statistical inference framework more complex.It is necessary to improve the state inference method of non-observed nodes.In the process of information dissemination of online social networks,the information propagation relationship is often attached to the information itself.Therefore,hidden information can be mined according to the state of the current network node.Based on the current state of network nodes,this paper proposed the concepts of relation topology and information topology and designed a candidate source expansion algorithm based on information topology.Based on this,this paper also pre-sented a malicious information locating algorithm based on Jordan center.Experiments on the generated network and real network show that the algorithm can effectively identify malicious information sources compared with other algorithms.

Key words: Malicious information source locating, Online social networks, Topological expansion

CLC Number:

TP309

YUAN De-yu, GAO Jian, YE Meng-xi, WANG Xiao-juan,. Malicious Information Source Locating Algorithm Based on Topological Extension in Online Social Network[J].Computer Science, 2019, 46(5): 129-134.

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Malicious Information Source Locating Algorithm Based on Topological Extension in Online Social Network

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