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Development of a Model for Spoofing Attacks in Internet of Things

Author

Listed:
  • Faheem Khan

    (Department of Computer Engineering, Gachon University, Seongnam 13120, Korea)

  • Abdullah A. Al-Atawi

    (Department of Computer Science, Applied College, University of Tabuk, Tabuk 47512, Saudi Arabia)

  • Abdullah Alomari

    (Department of Computer Science, Al-Baha University, Albaha 65799, Saudi Arabia)

  • Amjad Alsirhani

    (College of Computer and Information Sciences, Jouf University, Sakaka 72388, Saudi Arabia
    Faculty of Computer Science, Dalhousie University, Halifax, NS B3H 4R2, Canada)

  • Mohammed Mujib Alshahrani

    (College of Computing and Information Technology, University of Bisha, Bisha 61361, Saudi Arabia)

  • Jawad Khan

    (Department of Robotics, Hanyang University, Ansan 15588, Korea)

  • Youngmoon Lee

    (Department of Robotics, Hanyang University, Ansan 15588, Korea)

Abstract

Internet of Things (IoT) allows the integration of the physical world with network devices for proper privacy and security in a healthcare system. IoT in a healthcare system is vulnerable to spoofing attacks that can easily represent themselves as a legal entity of the network. It is a passive attack and can access the Medium Access Control address of some valid users in the network to continue malicious activities. In this paper, an algorithm is proposed for detecting spoofing attacks in IoT using Received Signal Strength (RSS) and Number of Connected Neighbors (NCN). Firstly, the spoofing attack is detected, located and eliminated through Received Signal Strength (RSS) in an inter-cluster network. However, the RSS is not useful against intra-cluster spoofing attacks and therefore the NCN is introduced to detect, identify and eliminate the intra-cluster spoofing attack. The proposed model is implemented in Network Simulator 2 (NS-2) to compare the performance of the proposed algorithm in the presence and absence of spoofing attacks. The result is that the proposed model increases the detection and prevention of spoofing.

Suggested Citation

  • Faheem Khan & Abdullah A. Al-Atawi & Abdullah Alomari & Amjad Alsirhani & Mohammed Mujib Alshahrani & Jawad Khan & Youngmoon Lee, 2022. "Development of a Model for Spoofing Attacks in Internet of Things," Mathematics, MDPI, vol. 10(19), pages 1-16, October.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3686-:d:936609
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    Cited by:

    1. Chen Chen & Shi Quan, 2022. "RSU Cluster Deployment and Collaboration Storage of IoV Based Blockchain," Sustainability, MDPI, vol. 14(23), pages 1-22, December.
    2. Kamran Taghizad-Tavana & Mohsen Ghanbari-Ghalehjoughi & Nazila Razzaghi-Asl & Sayyad Nojavan & As’ad Alizadeh, 2022. "An Overview of the Architecture of Home Energy Management System as Microgrids, Automation Systems, Communication Protocols, Security, and Cyber Challenges," Sustainability, MDPI, vol. 14(23), pages 1-23, November.

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