Affiliation:
1. Department of Computer Engineering, The Iraqi University, Baghdad 10011, Iraq
Abstract
Wireless video surveillance system is one of the cyber-physical security systems kinds, which transmits the signal of IP cameras through a wireless medium using a radio band. WVSSs are widely deployed with large systems for use in strategic places such as city centers, public transportation, public roads, airports, and play a significant role in critical infrastructure protection. WVSSs are vulnerable to jamming attacks creating an unwanted denial of service. Hence, it is essential to secure this system from jamming attacks. In this paper, three models of IoT-fuzzy inference system-based jamming detection system are proposed for detecting and countermeasure the presence of jamming by computing two jamming detection metrics; PDR and PLR, and based on the result, the system countermeasures this attack by storing the video feed locally in the subsystem nodes. FIS models are based on Mamdani, Tsukamoto, and Sugeno fuzzy logic which optimizes the jamming detection metrics for detecting the jamming attack. The efficiency of these proposed models is compared in detecting jamming signals. The experimental results show that the proposed Tsukamoto model detects jamming attacks with high accuracy and efficiency. Finally, the proposed IoT-Tsukamoto-based model was compared with the existing systems and proved to be superior to them in terms of central processing complexity, accuracy, and countermeasure for this attack.
Publisher
World Scientific Pub Co Pte Ltd
Subject
Computer Science Applications,Theoretical Computer Science,Software
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献