Cooperative Authentication in Underwater Acoustic Sensor Networks

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 physical and performance limitations, 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 estimated statistical channel parameters, 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.Comment: Author version of paper accepted for publication in the IEEE Transactions on Wireless Communication

Design of an Optimal Testbed for Tracking of Tagged Marine Megafauna

Underwater acoustic technologies are a key component for exploring the behavior of marine megafauna such as sea turtles, sharks, and seals. The animals are marked with acoustic devices (tags) that periodically emit signals encoding the device's ID along with sensor data such as depth, temperature, or the dominant acceleration axis - data that is collected by a network of deployed receivers. In this work, we aim to optimize the locations of receivers for best tracking of acoustically tagged marine megafauna. The outcomes of such tracking allows the evaluation of the animals' motion patterns, their hours of activity, and their social interactions. In particular, we focus on how to determine the receivers' deployment positions to maximize the coverage area in which the tagged animals can be tracked. For example, an overly-condensed deployment may not allow accurate tracking, whereas a sparse one, may lead to a small coverage area due to too few detections. We formalize the question of where to best deploy the receivers as a non-convex constraint optimization problem that takes into account the local environment and the specifications of the tags, and offer a sub-optimal, low-complexity solution that can be applied to large testbeds. Numerical investigation for three stimulated sea environments shows that our proposed method is able to increase the localization coverage area by 30%, and results from a test case experiment demonstrate similar performance in a real sea environment. We share the implementation of our work to help researchers set up their own acoustic observatory.Comment: Submitted for publication in Frontiers in Marine Science, special topic on Tracking Marine Megafauna for Conservation and Marine Spatial Plannin

Scalable adaptive networking for the Internet of Underwater Things

Internet of Underwater Things (IoUT) systems comprising tens or hundreds of underwater acoustic communication nodes will become feasible in the near future. The development of scalable networking protocols is a key enabling technology for such IoUT systems, but this task is challenging due to the fundamental limitations of the underwater acoustic communication channel: extremely slow propagation and limited bandwidth. The aim of this paper is to propose the JOIN protocol to enable the integration of new nodes into an existing IoUT network without the control overhead of typical state-of-the-art solutions. The proposed solution is based on the capability of a joining node to incorporate local topology and schedule information into a probabilistic model that allows it to choose when to join the network to minimize the expected number of collisions. The proposed approach is tested in numerical simulations and validated in two sea trials. The simulations show that the JOIN protocol achieves fast convergence to a collision-free solution, fast network adaptation to new nodes, and negligible network disruption due to collisions caused by a joining node. The sea trials demonstrate the practical feasibility of this protocol in real UAN deployments and provide valuable insight for future work on the trade-off between control overhead and reliability of the JOIN protocol in a harsh acoustic communication environment

Automated Detection of Dolphin Whistles with Convolutional Networks and Transfer Learning

Effective conservation of maritime environments and wildlife management of endangered species require the implementation of efficient, accurate and scalable solutions for environmental monitoring. Ecoacoustics offers the advantages of non-invasive, long-duration sampling of environmental sounds and has the potential to become the reference tool for biodiversity surveying. However, the analysis and interpretation of acoustic data is a time-consuming process that often requires a great amount of human supervision. This issue might be tackled by exploiting modern techniques for automatic audio signal analysis, which have recently achieved impressive performance thanks to the advances in deep learning research. In this paper we show that convolutional neural networks can indeed significantly outperform traditional automatic methods in a challenging detection task: identification of dolphin whistles from underwater audio recordings. The proposed system can detect signals even in the presence of ambient noise, at the same time consistently reducing the likelihood of producing false positives and false negatives. Our results further support the adoption of artificial intelligence technology to improve the automatic monitoring of marine ecosystems

A Survey of Techniques and Challenges in Underwater Localization

Underwater Wireless Sensor Networks (UWSNs) are expected to support a variety of civilian and military applications. Sensed data can only be interpreted meaningfully when referenced to the location of the sensor, making localization an important problem. While global positioning system (GPS) receivers are commonly used in terrestrial WSNs to achieve this, this is infeasible in UWSNs as GPS signals do not propagate through water. Acoustic communications is the most promising mode of communication underwater. However, underwater acoustic channels are characterized by harsh physical layer conditions with low bandwidth, high propagation delay and high bit error rate. Moreover, the variable speed of sound and the non-negligible node mobility due to water currents pose a unique set of challenges for localization in UWSNs. In this paper, we provide a survey of techniques and challenges in localization specifically for UWSNs. We categorize them into (i) range-based vs. range-free techniques; (ii) techniques that rely on static reference nodes vs. those who also rely on mobile reference nodes, and (iii) single-stage vs. multi-stage schemes. We compare the schemes in terms of localization speed, accuracy, coverage and communication costs. Finally, we provide an outlook on the challenges that should be, but have yet been, addressed. (C) 2011 Elsevier Ltd. All rights reserved

Spatial reuse scheduling and localization for underwater acoustic communication networks

Ocean exploration, through the development of ocean-observation systems, is a key step towards a fuller understanding of life on Earth. Underwater acoustic communication networks (UWANs) will help to fulfill the needs of these ocean-observation systems, whose applications include gathering of scientific data, early warning systems, ecosystem monitoring and military surveillance. The data derived from UWANs is typically interpreted with reference to the location of a data collecting node, e.g. when reporting an event occurrence, or the location of an object itself is of interest, e.g. when tracking a moving underwater vehicle or diver. In this dissertation, we develop methods for localization and efficient data exchange in UWANs. In the first part of this work, we focus on underwater localization (UWL). Since global positioning system signals do not propagate through water, UWL is often based on fusing information from acceleration-based sensors and ranging information to anchor nodes with known locations. We consider practical challenges of UWL. The propagation speed varies with depth and location, anchor and unlocalized nodes are not time-synchronized, nodes are moving due to ocean currents, propagation delay measurements for ranging of non-line-of-sight communication links are mistakenly identified as line-of-sight, and unpredictable changes in the ocean current makes it hard to determine motion models for tracking. Taking these features of UWL into account, we propose localization and tracking schemes that exploit the spatially correlated ocean current, nodes' constant motion, and the periodicity of ocean waves. In the second part of this thesis, we use location information to develop medium access control scheduling algorithms and channel coding schemes. We focus on adaptive scheduling in which each node transmits based on timely network information. Specifically, our scheduling algorithms utilize the long propagation delay in the channel and the sparsity of the network topology to improve throughput, reliability and robustness to topology changes. To evaluate performance, we have developed a simulator combining existing numerical models of ocean current and of power attenuation in the ocean. We have also verified simulation results in four sea experiments of different channel bathymetry structures, using both industry and self-developed underwater acoustic modems.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat

A Graph Localization Approach for Underwater Sensor Networks to Assist a Diver in Distress

In this paper, we focus on the problem of locating a scuba diver in distress using a sensor network. Without GPS reception, submerged divers in distress will transmit SOS messages using underwater acoustic communication. The study goal is to enable the quick and reliable location of a diver in distress by his fellow scuba divers. To this purpose, we propose a distributed scheme that relies on the propagation delay information of these acoustic SOS messages in the scuba divers’ network to yield a range and bearing evaluation to the diver in distress by any neighboring diver. We formalize the task as a non-convex, multi-objective graph localization constraint optimization problem. The solution finds the best configuration of the nodes’ graph under constraints in the form of upper and lower bounds derived from the inter-connections between the graph nodes/divers. Considering the need to rapidly propagate the SOS information, we flood the network with the SOS packet, while also using rateless coding to leverage information from colliding packets, and to utilize time instances when collisions occur for propagation delay evaluation. Numerical results show a localization accuracy on the order of a few meters, which contributes to quickly locating the diver in distress. Similar results were demonstrated in a controlled experiment in a water tank, and by playback data from a sea experiment for five network topologies