Abstract:
In underwater acoustic sensor networks (UASNs), source nodes serving as data centers hold significant commercial value and strategic importance, and the leakage of their ...Show MoreMetadata
Abstract:
In underwater acoustic sensor networks (UASNs), source nodes serving as data centers hold significant commercial value and strategic importance, and the leakage of their location information may result in immeasurable negative consequences. Presently, the methods employed to protect the location privacy of source nodes within UASNs face challenges such as limited network security duration, high node energy consumption, and prolonged data transmission delays. Additionally, security research has predominantly focused on passive attacks, with insufficient provisions against active threats. To address these issues, this study proposes a polygonal phantom source position privacy protection algorithm based on a secure zone (PPSZ) in autonomous underwater vehicle (AUV)-aided UASNs. First, a polygonal secure zone is defined with the source node at its center. Phantom nodes are strategically selected from nodes situated outside this zone, leveraging the relative angles between nodes to deter passive attacks while mitigating data transmission delays. Next, the selection of relay nodes is optimized using the Q-learning algorithm, where each node adjusts its selection strategy based on real-time feedback, further lowering node energy consumption. Finally, auxiliary nodes are deployed using a nonuniform clustering strategy to collectively transmit interference signals, effectively disrupt active attacks, and ensure the secure transmission of source data. Simulation results demonstrate that the PPSZ algorithm can better balance the relationships among safety time, node energy consumption, and data transmission delays.
Published in: IEEE Transactions on Intelligent Transportation Systems ( Early Access )