Enhanced Secure AODV for Real-Time loT WSN Applications under Black Hole and Selective Forwarding Attacks
Keywords:
Internet of Things (IoT) , Wireless Sensor Networks (WSNs) , Ad Hoc On-Demand Distance Vector (AODV) , Enhanced Secure AODV and Machine Learning.Abstract
The rapid advancement of the Internet of Things (IoT) has led to the widespread deployment of Wireless Sensor Networks (WSNs) in various real-time applications, including healthcare monitoring, industrial automation, environmental surveillance, smart agriculture, and intelligent transportation systems. These applications require reliable, secure, and energy-efficient communication among sensor nodes. However, the open and decentralized architecture of IoT-enabled WSNs makes them highly vulnerable to routing attacks such as Black Hole and Selective Forwarding attacks. These attacks can significantly degrade network performance by increasing packet loss, reducing throughput, disrupting communication reliability, and compromising Quality of Service (QoS). The traditional Ad Hoc On-Demand Distance Vector (AODV) routing protocol lacks sufficient security mechanisms to effectively identify and mitigate such malicious activities, making it unsuitable for secure real-time IoT environments.
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