Evaluating the Propagation Strength of Malicious Metaphor in Social Network: Flow Through Inspiring Influence of Members

  • Manash Sarkar
  • Soumya Banerjee
  • Aboul Ella Hassanien
Part of the Intelligent Systems Reference Library book series (ISRL, volume 65)


Interaction across social networking sites leads to different kinds of ideas, concepts and choices and sharing or some nourishing effects, which might influence others to believe or trust. Seldom may this cause some malicious effect for members and their peers only. As social network is the domain for sharing opinion and comments, subsequently it can also propagate malicious signature as well. Security and privacy is essential component to protect user profile from this kind of malicious program, which basically evolves from any close acquaintances, that also belongs to same vector plane. The degree of malicious attack of a social network depends on the number of flow links from one user to another with forward operations. It is true that the probability of malicious attack evolves from friend’s community is of greater attack prone magnitude than the degree of attack from unknown members. This paper focuses the different verticals of such possibilities of attack under social network processes and also tries to investigate the rudimentary precautionary measure pertaining security algorithm behind it.


Degree of Attack Social Network Attack Graph Conditional Probability Gaussian distribution 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Manash Sarkar
    • 1
  • Soumya Banerjee
    • 1
  • Aboul Ella Hassanien
    • 2
  1. 1.Department of Computer ScienceBirla Institute of TechnologyMesraIndia
  2. 2.Faculty of Computers and InformationCairo UniversityCairoEgypt

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