Preserving Data Integrity and Security in IoT-Enabled Wireless Sensor Networks: Employing an Intrusion Detection System Strategy
M. Vaithiyanathan, Naduvathezhath Nessariose Jose, C.S. Sasireka, Pooja Mishra, T. Prabahar Godwin James, Nookala Venu · 2024
The proliferation of IoT-enabled wireless sensor networks (WSNs) has ushered in a multitude of applications but has also heightened concerns regarding data integrity and security. This underscores the critical necessity for robust Intrusion Detection Systems (IDS) tailored explicitly for such environments. This study presents an innovative IDS framework designed to safeguard the integrity and security of data within -enabled. Our IDS framework introduces advanced machine learning techniques and anomaly detection algorithms to enable real-time monitoring and analysis, effectively identifying and mitigating potential threats. Through extensive experimentation and validation, we demonstrate the reliability and efficacy of our IDS in detecting various intrusion attempts while minimizing false alarms. Moreover, our framework incorporates adaptive mechanisms to address evolving threats and network dynamics, ensuring continuous protection against malicious activities. By enhancing the resilience of IoT-enabled WSNs against intrusions, our research contributes to bolstering trust and reliability in critical applications.