Detecting Malicious Users and Remove Rumors from Social Network

  • Authors

    • Dr V.Manjula
    • Mrs. Shanmuga Priya
    • V Divyaprabha
    • S Jayasurya
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.34.19208
  • Data mining, detection, malicious user, Reverse dissemination, social network.

  • Perceiving tattle sources in casual associations expect an essential part in obliging the damage caused by them through the timely disengage of the sources. In any case, the short lived assortment in the topology of casual associations and the advancing dynamic processes challenge our standard source recognizing confirmation strategies that are considered in static frameworks. We diminish the time-varying networks to a movement of static frameworks by introducing a period consolidating window. By then instead of looking at each individual in standard techniques, we grasp a rearrange dispersing framework to demonstrate a game plan of suspects of the certified talk source.

     

     

  • References

    1. [1] Wei Chen Microsoft Research Asia Beijing, China weic@microsoft.com Chi Wang University of Illinois at Urbana-Champaign, USA chiwang1@illinois.edu Yajun Wang Microsoft Research Asia Beijing, China yajunw@microsoft.com “Scalable Influence Maximization for Prevalent Viral Marketing in Large-Scale Social Networks†July 25 - 28, 2010.

      [2] Ceren budak, Department of Computer Science, UCSB Santa Barbara, USA cbudak@cs.ucsb.edu Divyakant Agrawal Department of Computer Science, UCSB Santa Barbara, USA agrawal@cs.ucsb.edu Amr El Abbadi Department of Computer Science, UCSB Santa Barbara, USA amr@cs.ucsb.edu “Limiting the Spread of Misinformation in Social Networks†March 28 - April 01, 2011 .

      [3] Sundong Kim supervised by Jae-Gil Lee Expected graduation date: Feb, 2018 Korea Advanced Institute of Science and Technology, Daejeon, Korea Friend “Recommendation with a Target User in Social Networking Services†Feb, 2018.

      [4] Bita Azimdoost, Hamid R. Sadjadpour, Senior Member, IEEE, and J. J. Garcia-Luna-Aceves, Fellow, IEEE “Capacity of Wireless Networks with Social Behavior “January 2013â€.

      [5] Xin Rong School of Information University of Michigan ronxin@umich.edu Qiaozhu Mei School of Information University of Michigan qmei@umich.edu “Diffusion of Innovations Revisited: From Social Network to Innovation Network†published in 2013.

      [6] Mohsen Karimzadeh Kiskaniy, Bita Azimdoosty, and Hamid R. Sadjadpoury,†Effect of Social Groups on the Capacity of wireless networks†Aug 2015.David KempeDept. of Computer ScienceCornell University, “Maximizing the Spread of Influence through a Social networksâ€August 24 - 27, 2003 .

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  • How to Cite

    V.Manjula, D., Shanmuga Priya, M., Divyaprabha, V., & Jayasurya, S. (2018). Detecting Malicious Users and Remove Rumors from Social Network. International Journal of Engineering & Technology, 7(3.34), 283-286. https://doi.org/10.14419/ijet.v7i3.34.19208