A Prevention Strategy Against Rumor Spreading in Complex Networks

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Sadati, Hoda | 2013

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Type of Document: M.Sc. Thesis
Language: English
Document No: 44292 (52)
University: Sharif University of Technology, International Campus, Kish Island
Department: Science and Engineering
Advisor(s): Khansari, Mohammad
Abstract:
Complex networks have recently become a very noticeable subject because of their remarkable theory on real networks such as rumor spreading. This thesis contributes to a prevention strategy which uses a maximal clique algorithm to find overlapping communities and also uses inverse targeting immunization strategy to immune these communities. By the using maximal clique algorithm combined with inverse targeting strategy we have achieved that the TIK method (targeted immunization using k-clique percolation) obtains 10% of better immunization than HD (highest degree) method which is one of the best methods in targeted immunization strategies. The TIK also demonstrates that rumor spreading is significantly slowed down to zero due to using the k-clique percolation algorithm in the rumor model
Keywords:
Community Detection ; Complex Network ; Rumor Spreading ; K-Clique Percolation Algorithm ; Targeted Immunization

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