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An information theory based approach for identifying influential spreaders in temporal networks

conference contribution
posted on 2017-01-01, 00:00 authored by L Luo, L Tao, H Xu, Z Yuan, H Lai, Zili ZhangZili Zhang
Identifying the most influential nodes in computer networks is an important issue in preventing the spread of computer viruses. In order to quantify the importance of nodes in the spreading of computer viruses, various centrality measures have been developed under an assumption of a static network. These measures have limitations in that many network structures are dynamically change over time. In this paper, we extend an entropy-based centrality from time-independent networks to time-dependent networks by taking into account the temporal and spatial connections between different nodes simultaneously. We also propose an algorithm for ranking the influences of nodes. According to the experimental results on three synthetic networks and a real network for susceptible-infected-recovered (SIR) spreading model, our proposed temporal entropy-based centrality (TEC) is more accurate than existing temporal betweenness, and closeness centralities.

History

Event

Cyberspace safety and security. International symposium (9th : 2017 : Xi'an, China)

Volume

10581

Series

Lecture notes in computer science

Pagination

477 - 484

Publisher

Springer

Location

Xi'an, China

Place of publication

Cham, SWitzerland

Start date

2017-10-23

End date

2017-10-25

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319694702

Language

eng

Publication classification

E Conference publication; E1.1 Full written paper - refereed

Copyright notice

2017, Springer International Publishing AG.

Editor/Contributor(s)

Sheng Wen, Wei Wu, Aniello Castiglione

Title of proceedings

CSS 2017 : Proceedings of the 9th International Symposium

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