Intrusion Detection System To Counter Sybil Attacks In Underwater Wireless Sensor Networks Using Isolation Forest

Underwater Wireless Sensor Networks (UWSNs) are increasingly deployed in maritime and environmental monitoring, data gathering, and underwater communication. However, their unique characteristics—limited bandwidth, high latency, and energy constraints—make UWSNs highly susceptible to security threats, particularly the Sybil attack. In a Sybil attack, a malicious node forges multiple identities, compromising network integrity and leading to false data propagation and resource exhaustion. This paper proposes an Intrusion Detection System (IDS) that leverages the Isolation Forest algorithm to counter Sybil attacks in UWSNs. By analyzing node behavior, the proposed IDS identifies anomalies that correspond to Sybil nodes. The Isolation Forest algorithm is well-suited for this purpose due to its unsupervised nature and efficiency in detecting outliers, making it ideal for the constrained environment of UWSNs. Experimental results show that the proposed IDS effectively identifies Sybil nodes with high accuracy and low computational overhead, enhancing network security without compromising performance. This approach represents a significant advancement in safeguarding UWSNs against malicious intrusions, enabling more secure and reliable underwater operations.