Enhancing the security of patients' portals and websites by detecting malicious web crawlers using machine learning techniques.

Journal: International journal of medical informatics
Published Date:

Abstract

INTRODUCTION: There is increasing demand for access to medical information via patients' portals. However, one of the challenges towards widespread utilisation of such service is maintaining the security of those portals. Recent reports show an alarming increase in cyber-attacks using crawlers. These software programs crawl web pages and are capable of executing various commands such as attacking web servers, cracking passwords, harvesting users' personal information, and testing the vulnerability of servers. The aim of this research is to develop a new effective model for detecting malicious crawlers based on their navigational behavior using machine-learning techniques.

Authors

  • Nafiseh Hosseini
    Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. Electronic address: Hoseinin951@mums.ac.ir.
  • Fatemeh Fakhar
    Department of Computer Science, Faculty of Engineering, Payame Noor University (PNU), Iran. Electronic address: Fakhar.mshd@gmail.com.
  • Behzad Kiani
    Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. Electronic address: KianiB@mums.ac.ir.
  • Saeid Eslami
    Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.