A fuzzy logic-based secure hierarchical routing scheme using firefly algorithm in Internet of Things for healthcare.

Journal: Scientific reports
Published Date:

Abstract

The Internet of Things (IoT) is a universal network to supervise the physical world through sensors installed on different devices. The network can improve many areas, including healthcare because IoT technology has the potential to reduce pressure caused by aging and chronic diseases on healthcare systems. For this reason, researchers attempt to solve the challenges of this technology in healthcare. In this paper, a fuzzy logic-based secure hierarchical routing scheme using the firefly algorithm (FSRF) is presented for IoT-based healthcare systems. FSRF comprises three main frameworks: fuzzy trust framework, firefly algorithm-based clustering framework, and inter-cluster routing framework. A fuzzy logic-based trust framework is responsible for evaluating the trust of IoT devices on the network. This framework identifies and prevents routing attacks like black hole, flooding, wormhole, sinkhole, and selective forwarding. Moreover, FSRF supports a clustering framework based on the firefly algorithm. It presents a fitness function that evaluates the chance of IoT devices to be cluster head nodes. The design of this function is based on trust level, residual energy, hop count, communication radius, and centrality. Also, FSRF involves an on-demand routing framework to decide on reliable and energy-efficient paths that can send the data to the destination faster. Finally, FSRF is compared to the energy-efficient multi-level secure routing protocol (EEMSR) and the enhanced balanced energy-efficient network-integrated super heterogeneous (E-BEENISH) routing method based on network lifetime, energy stored in IoT devices, and packet delivery rate (PDR). These results prove that FSRF improves network longevity by 10.34% and 56.35% and the energy stored in the nodes by 10.79% and 28.51% compared to EEMSR and E-BEENISH, respectively. However, FSRF is weaker than EEMSR in terms of security. Furthermore, PDR in this method has dropped slightly (almost 1.4%) compared to that in EEMSR.

Authors

  • Mehdi Hosseinzadeh
    School of Computer Science, Duy Tan University, Da Nang, 550000, Viet Nam; Jadara Research Center, Jadara University, Irbid 21110, Jordan. Electronic address: mehdihosseinzadeh@duytan.edu.vn.
  • Joon Yoo
    School of Computing, Gachon University, 1342 Seongnamdaero, Seongnam, 13120, South Korea.
  • Saqib Ali
    Faculty of Information Technology, Beijing University of Technology, Beijing, People's Republic of China.
  • Jan Lansky
    Department of Computer Science and Mathematics, Faculty of Economic Studies, University of Finance and Administration, Prague, Czech Republic.
  • Stanislava Mildeova
    Department of Computer Science and Mathematics, Faculty of Economic Studies, University of Finance and Administration, Prague, Czech Republic.
  • Mohammad Sadegh Yousefpoor
    Department of Computer Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran.
  • Omed Hassan Ahmed
    Department of Information Technology, University of Human Development, Sulaymaniyah, Iraq.
  • Amir Masoud Rahmani
    Future Technology Research Center, National Yunlin University of Science and Technology, Yunlin, Taiwan. rahmania@yuntech.edu.tw.
  • Lilia Tightiz
    School of Computing, Gachon University, 1342 Seongnamdaero, Seongnam, 13120, South Korea. liliatightiz@gachon.ac.kr.