A worm-containing strategy using a social network and PageRank

  • Authors:
  • Donghwa Kang;Daeshin Park;Yookun Cho

  • Affiliations:
  • Seoul National University Seoul, Korea;Soongsil University Seoul, Korea;Seoul National University Seoul, Korea

  • Venue:
  • Proceedings of the 2013 Research in Adaptive and Convergent Systems
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Recently, more and more worms are propagating through social networks. By exploiting the high connectivity of social networks, malicious users are able to propagate their social network based worms faster than worms based on other networks. Zhichao presented a patch distribution scheme using key nodes to restrict worm activities. Their scheme analyzes the network structure and repeatedly selects key nodes as initial patch distributors. We propose a modified selection strategy for key nodes based on a PageRank calculation. Our strategy eliminates unnecessary overhead involved in the Zhichao's selection process. Using the PageRank calculation, only one node is selected for each sub-graph in our strategy. Experimental results show that our strategy allowed lower maximum infection rate than Zhichao's scheme.