TSN-SLP: A Trusted Sybil Node-based Source Location Privacy Scheme using Evidence Theory in Underwater Sensor Networks

The security of underwater sensor networks (USNs) is challenging in ocean research. The primary objective of this work is to investigate the susceptibility of USNs to passive attacks, such as source location privacy (SLP). A trusted Sybil node-based source location scheme is introduced in this manuscript to fulfil the above purpose. The Sybil nodes and suitable fake source nodes are initially inserted into a network. The main intention is to generate false source data by using fake source nodes generated with evidence theory for data fusion, thereby disguising the traffic carried by the source information. After that, separate transmission windows were scheduled for the real and false packets to prevent data conflicts. The Sybil nodes are also used during the multi-path data routing process, which occurs from the source node to the destination node. In addition to diversifying the routes, it raises the bar for the adversary's ability to track the source information's route while it is being sent without conflict. The proposed TSN-SLP scheme outperformed SLPRRFPR, EECOR, and ARR by 21%, 53%, 50%, and 17.4%, respectively, in average packet data rate, safety time, transmission delay, and energy use, according to the experimental results.