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2000
Volume 15, Issue 2
  • ISSN: 2210-3279
  • E-ISSN: 2210-3287

Abstract

Background and Objective

The Internet of Things offers ubiquitous automation of things and makes human life easier. Sensors are deployed in the connected environment that sense the medium and actuate the control system without human intervention. However, the tiny connected devices are prone to severe security attacks. As the Internet of Things has become evident in everyday life, it is very important that we secure the system for efficient functioning.

Methods

This paper proposes a secure federated learning-based protocol for mitigating BH attacks in the network.

Results

The experimental result proves that the intelligent network detects BH attacks and segregates the nodes to improve the efficiency of the network. The proposed techniques show improved accuracy in the presence of malicious nodes.

Conclusion

The performance is also evaluated by varying the attack frequency time.

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/content/journals/swcc/10.2174/0122103279285078240212063010
2024-03-04
2025-10-30
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