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  Web Robot Detection Based On Fuzzy System and PSO Algorithm  
  Authors : Mohammad Ordouei; Iman Namdar
  Cite as:


Web robots are applications which recursively and automatically overview the content of website documents. Some robots are considered to be malicious. Hence, identifying web robots is a classification challenge. In this research we mainly present a hybrid particle swarm optimization method and fuzzy system aiming at increasing efficiency over Web robot detection and simulation by MATLAB software. Evaluation criteria are considered: Specificity, Accuracy, F- Measure, Recall and Precision. Results of the study for the proposed method are respectively: 99.81, 96.92, 96.10, 91.39 and 99.58. The yields for proposed basic fuzzy system and fuzzy network algorithm and ANFIS neural fuzzy network algorithm indicate the priority of the proposed method other than algorithms being compared.


Published In : IJCSN Journal Volume 7, Issue 4

Date of Publication : August 2018

Pages : 272-278

Figures :07

Tables : 03


Mohammad Ordouei : Computer Engineering Dep., Islamic Azad University (IAU) Tehran,Iran

Iman Namdar : Computer Engineering Dep., Islamic Azad University (IAU) Tehran,Iran


Web robot detection; fuzzy system; particle swarm optimization algorithm

This paper aimed at providing a hybrid method to improve web robots accuracy. Of the features of proposed method than similar works we consider: - Providing a novel method to detect Web robots influence - Improve efficiency detecting web robots The paper investigated through MATLAB software, the results were compared using algorithms. To test the performance of the proposed method some criteria including Precision, Accuracy, F-Measure, Recall and Specificity were considered. Conducting experiments yielded that the proposed algorithm was better than the other ones.


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