Name
Abstract | ||
|---|---|---|
With the growing use of underwater acoustic communications (UWAC) for both industrial and military operations, there is a need to ensure communication security. A particular challenge is represented by underwater acoustic networks (UWANs), which are often left unattended over long periods of time. Currently, due to the physical and performance limitations, the UWAC packets rarely include encryption, leaving the UWAN exposed to external attacks faking legitimate messages. In this paper, we propose a new algorithm for message authentication in a UWAN setting. We begin by observing that, due to the strong spatial dependency of the underwater acoustic channel, an attacker can attempt to mimic the channel associated with the legitimate transmitter only for a small set of receivers, typically just for a single one. Taking this into account, our scheme relies on trusted nodes that independently help a sink node in the authentication process. For each incoming packet, the sink fuses beliefs evaluated by the trusted nodes to reach an authentication decision. These beliefs are based on the estimated statistics of the channel parameters, which are chosen to be the most sensitive to the transmitter-receiver displacement. Our simulation results show accurate identification of an attacker’s packet. We also report results from a sea experiment demonstrating the effectiveness of our approach. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TWC.2018.2886896 | IEEE Transactions on Wireless Communications |
Keywords | Field | DocType |
Authentication,Channel estimation,Underwater acoustics,Transmitters,Wireless communication,Receivers | Authentication,Wireless,Message authentication code,Network packet,Computer network,Underwater acoustics,Communication channel,Encryption,Real-time computing,Mathematics,Communications security | Journal |
Volume | Issue | ISSN |
abs/1806.02628 | 2 | 1536-1276 |
Citations | PageRank | References |
0 | 0.34 | 28 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roee Diamant | 1 | 67 | 13.52 |
| Paolo Casari | 2 | 27 | 4.84 |
| Stefano Tomasin | 3 | 1145 | 102.92 |