Underwater Networking and MUAC Masked Underwater Acoustic Communication POCs: Justin Rohrer [PI] (jprohrer@nps.edu) Carl Prince (cdprince@nps.edu)

Importance The underwater domain is becoming an increasingly important area for the Navy. There are important systems at sea that can not give away their location: Underwater Gliders Underwater sensors Underwater drones Manned submarines There needs to be a network to land in order to facilitate information this network may involve routers/hubs, etc. Modeling this network is important

Underwater Networking Create an underwater software defined network U-SDN, modeling underwater delays include detectors both fixed and movable Map out how devices will connect and communicate to the land Design of infrastructure

Use cases Sensors transmitting OK -- location and good operation, nothing found – can be performed with very minimal data rates, is performed relatively often compared to sending detection data, it is important that this is performed so as not to be detected Transmitting detection data – more important data, non-trivial data amounts may need to be sent relatively quickly

MUAC Masking Sounds Since some underwater devices can not give away their location we must communicate in a way such that the communication is undetectable, this can be performed using masking sounds: Biologics dolphins shrimp whales crabs other Naturally occurring sounds bubbles water underwater background noise earth quake noise

Acoustical Communication Native acoustic communication can be performed by Putting together sounds to send symbols Using sound segments to send multiple symbols Data rates can be more than ‘transmitting OK’ Native acoustics as a carrier wave with steganographic data sent on the carrier wave to achieve a low probability of detection [Passerieux] Data rates are very slow, 1-4 symbols per sec, but very hard to detect Can send on naturally occurring sounds travel distance can be characterized as shorter Can send on biologics Travel distance can be longer Current method based on Passerieux Patent US20170149522A1

Current Work Focused on steganography, or the data hiding art of hiding messages in plain sight. Use of spread spectrum using steganography to send messages Steganographic algorithm is implemented by hiding bits/symbols in phase centered on a carrier frequency (signal processing). The carrier transmission masks the underlying message. Carrier transmissions are previously recorded or database stored sound clips in order to be representative of current environment and background noise conditions – can be ambient discrete, or continuous, and natural, or biologics Exploring effects of modulation schemes on data rates and imperceptibility. Goal is to send data and to recover messages, while at the same time being undetected by a trained adversary sonar operator with time-frequency displays. Optimize which carrier sounds act as the best covers and trade offs of distance traveled vs. perceptibility.

MUAC Future Work There is no one chosen model in published work, there are many models used to model communication, is there an optimal model – a model that is accurate and able to model transmission using time and frequency domains? The current method the student has working is a bi-polar model, can we use a quadrature-polar model? Currently we use 360 degrees as one cycle, can we create a timing algorithm to include non-360 degree cycles to make detection even harder? Are there better steganographic or covert waveform approaches to Passerieux’s covert UAC? Can we make an algorithm or modulation scheme improvement(s) for robustness, embedding efficiency, imperceptibility? How good is our method of steganalyis – need a detailed statistical analysis of artifacts as a result of the embedding algorithm, and or how to attack this scheme? Will our method actually work at sea – testing? Can this scheme be implemented -- take the results of this study, once proven feasible, and find a way to bridge the gap with a program of record Navy system onboard ships, submarines, sonobouys, etc.