AUV-Assisted Stratified Source Location Privacy Protection Scheme Based on Network Coding in UASNs

Abstract

The position of the source is sensitive and critical information in underwater acoustic sensor networks (UASNs). In this study, a network coding-based scheme called the stratified source location privacy protection scheme (SSLP-NC) with autonomous underwater vehicle (AUV) is suggested for a strong adversary that can decode data. First, for the adversary with passive attacks, several fake source selection algorithms are suggested for two circumstances where the source is in the shallow and deep sea, respectively. Each node then utilizes a pseudo-random number generator to create sequences on a regular basis so that the key data can be delivered to the sink without interference. Then, for the adversary with active attack, the node encrypts the source and fake data using the preexisting pseudo-random number sequence as an encoding vector to thwart the adversary’s decryption. Further, this work develops a relay node selection approach for transmitting the encoded data, which increases the variety of the data transmission pathways. Finally, this study includes a hole avoidance strategy that uses nodes or an AUV to address the potential hole issue. The simulation demonstrates that the SSLP-NC successfully fends off an adversary that can decode data packets, and performs better than the EECOR and DBR-MAC algorithms in terms of network safe time and packet delivery rate.