Underwater Wireless Sensor Networks (UWSNs) hold significant economic and military value; however, their routing protocols remain inherently vulnerable to external attacks. Unlike terrestrial networks, UWSNs cannot readily adopt complex cryptographic verification systems due to the high propagation delay, limited bandwidth, and low connectivity inherent in underwater acoustic channels. To address the wormhole attack—one of the most critical threats to UWSN routing—this paper proposes an intelligent routing scheme (UWSN-IRS) that not only detects wormhole attacks effectively but also identifies the source nodes and eliminates the threat. The proposed scheme comprises four integrated modules: a self-adjusting routing mechanism, a wormhole attack detection mechanism, a wormhole node localization mechanism, and an anti-cheating mechanism. The self-adjusting routing mechanism optimizes node distribution and intelligently searches for the optimal forwarding path. Upon the occurrence of a wormhole attack, the detection mechanism employs an artificial neural network to identify the compromised links and outputs a set of suspected wormhole nodes. Subsequently, the localization mechanism determines the exact positions of these malicious nodes through ranging and iterative positioning. Finally, the anti-cheating mechanism isolates the detected attacking nodes and deploys substitute nodes to fill the resulting monitoring voids. The experimental results demonstrate that the UWSN-IRS exhibits superior performance in attack scenarios, enabling reliable wormhole detection, precise attacker localization, and sustained normal network communication.
Chen et al. (Thu,) studied this question.