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Observing Consistency in Online Communication Patterns for User Re-Identification

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  • Ikuesan Richard Adeyemi
  • Shukor Abd Razak
  • Mazleena Salleh
  • Hein S Venter

Abstract

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas.

Suggested Citation

  • Ikuesan Richard Adeyemi & Shukor Abd Razak & Mazleena Salleh & Hein S Venter, 2016. "Observing Consistency in Online Communication Patterns for User Re-Identification," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-27, December.
    • Handle: RePEc:plo:pone00:0166930
    DOI: 10.1371/journal.pone.0166930
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    References listed on IDEAS

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    3. Albert-László Barabási, 2005. "The origin of bursts and heavy tails in human dynamics," Nature, Nature, vol. 435(7039), pages 207-211, May.
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