Development of a Model for Spoofing Attacks in Internet of Things

Faheem Khan (), Abdullah A. Al-Atawi, Abdullah Alomari, Amjad Alsirhani, Mohammed Mujib Alshahrani, Jawad Khan and Youngmoon Lee ()
Additional contact information
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
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

Mathematics, 2022, vol. 10, issue 19, 1-16

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.

Keywords: spoofing attack; IoT; RSS; NCN; healthcare system; NS-2 simulator (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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