On the Use of Conversation Detection to Improve the Security of Underwater Acoustic Networks

Security is one of the key aspects of underwater acoustic networks, due to the critical importance of the scenarios in which these networks can be employed. For example, attacks performed to military underwater networks or to assets deployed for tsunami prevention can lead to disastrous consequences. Nevertheless, countermeasures to possible network attacks have not been widely investigated so far. One way to identify possible attackers is by using reputation, where a node gains trust each time it exhibits a good behavior, and loses trust each time it behaves in a suspicious way. The first step for analyzing if a node is behaving in a good way is to inspect the network traffic, by detecting all conversations. This paper proposes both centralized and decentralized algorithms for performing this operation, either from the network or from the node perspective. While the former can be applied only in post processing, the latter can also be used in real time by each node, and so can be used for creating the trust value. To evaluate the algorithms, we used real experimental data acquired during the EDA RACUN project (Robust Underwater Communication in Underwater Networks).