Social Relationships and Temp-Spatial Behaviors Based Community Discovery to Improve Cyber Security Practices

IEEE Access

Shancang Li¹  Biwei Cao²  Muddesar Iqbal³  Bo Liu⁴  Weijia Liu⁵  Jiuxin Cao⁵  Pan Wang⁶ 

[1] Department of Computer Science and Creative Technologies, University of the West of England, Bristol, U.K.;Department of Computer Science, The Australia National University, Canberra, ACT, Australia;School of Computer Science and Electronic Engineering, University of Essex, Colchester, U.K.;School of Computer Science and Engineering, Southeast University, Nanjing, China;School of Cyber Science and Engineering, Southeast University, Nanjing, China;Southeast University-Monash University Suzhou Joint Graduate School, Suzhou, China;

关键词: Location-based service;    social network;    homogeneous social network;    community discovery;    cyber security;   

DOI  :  10.1109/ACCESS.2019.2931937

来源: DOAJ

【 摘 要 】

Cyber security significantly relies on the dynamic communities in social networks. The location-based social network (LBSN) is a new type of social system that has sprung up recently that. It turns traditional social networks into heterogeneous networks by incorporating location information, which is used as the medium between the real world and the online social networks, thus bringing new challenges to the community discovery problems. This paper proposes a LBSN homogeneous network model (LSHNM) based on the user social relations and temp-spatial behaviors to calculate the user similarity relations in multi-dimensional features and construct LBSN isomorphism network topology, which can be used to improve cyber security practices. After that non-negative matrix decomposition (NMF) is used to find communities from above isomorphism network topology. The experimental results show that the LSHNM can find more satisfactory community structures.

【 授权许可】

Unknown