More Web Proxy on the site http://driver.im/

research-article

Open access

Physical Layer Authentication in Underwater Acoustic Networks with Mobile Devices

Authors:

Francesco Ardizzon,

Stefano TomasinAuthors Info & Claims

WUWNet '22: Proceedings of the 16th International Conference on Underwater Networks & Systems

Article No.: 4, Pages 1 - 8

https://doi.org/10.1145/3567600.3567604

Published: 29 December 2022 Publication History

All formats PDF

Abstract

As underwater acoustic communication technologies become mature and underwater networks evolve into reliable solutions for data communications, authenticating transmitted data turns from an option to a necessity. In this paper, we explore physical-layer authentication for an underwater acoustic networks with mobile devices. We choose the power-weighted average of the channel taps’ arrival delay as the main authentication feature. We then develop a Kalman filter approach to track the evolution of this feature in the presence of mobility. The filter computes an innovation metric for each new transmission, which is processed to determine if a signal originates from a legitimate network node. Simulation results obtained from a dataset generated with Bellhop show that our authentication mechanism successfully distinguishes between legitimate and impersonating transmitters. Moreover, we show that linearly combining innovation readings from multiple sensors yields a good low-complexity classifier, and assess the impact of the transmitter speed on the authentication performance.

References

[1]

Ahmed Al Guqhaiman, Oluwatobi Akanbi, Amer Aljaedi, and C. Edward Chow. 2020. Lightweight Multi-factor Authentication for Underwater Wireless Sensor Networks. In Proc. CSCI. IEEE, Las Vegas, NV, USA, 188–194.

[2]

Waqas Aman, Zeeshan Haider, S. Waqas H. Shah, M. Mahboob Ur Rahman, and Octavia A. Dobre. 2020. On the Effective Capacity of an Underwater Acoustic Channel under Impersonation Attack. In Proc. IEEE ICC. IEEE, Dublin, Ireland.

[3]

F. Ardizzon, S. Tomasin, R. Diamant, and P. Casari. 2022. Machine Learning-Based Distributed Authentication of UWAN Nodes With Limited Shared Information. In Proc. UCOMMS. Lerici, Italy.

[4]

L. Bragagnolo, F. Ardizzon, N. Laurenti, P. Casari, R. Diamant, and S. Tomasin. 2021. Authentication of Underwater Acoustic Transmissions via Machine Learning Techniques. In Proc. IEEE COMCAS. IEEE, Tel Aviv, Israel, 255–260.

[5]

Alessandro Brighente, Francesco Formaggio, Giorgio Maria Di Nunzio, and Stefano Tomasin. 2019. Machine Learning for In-Region Location Verification in Wireless Networks. IEEE Journal on Selected Areas in Communications 37, 11(2019), 2490–2502.

Digital Library

[6]

Zhongyue Chen, Huifang Chen, and Wen Xu. 2014. Simplified time synchronization for underwater acoustic sensor networks with high propagation latency. In Proc. MTS/IEEE OCEANS. IEEE, Taipei, Taiwan, 1–5.

[7]

Young-Sik Choi. 2009. Least Squares One-Class Support Vector Machine. Pattern Recogn. Lett. 30, 13 (oct 2009), 1236–1240.

Digital Library

[8]

R. Diamant. 2016. Closed Form Analysis of the Normalized Matched Filter With a Test Case for Detection of Underwater Acoustic Signals. IEEE Access 4(2016), 8225–8235.

[9]

Roee Diamant, Paolo Casari, and Stefano Tomasin. 2019. Cooperative Authentication in Underwater Acoustic Sensor Networks. IEEE Trans. Wireless Commun. 18, 2 (2019), 954–968.

Digital Library

[10]

Roee Diamant and Lutz Lampe. 2013. Underwater Localization with Time-Synchronization and Propagation Speed Uncertainties. IEEE Trans. Mobile Comput. 12, 7 (2013), 1257–1269.

Digital Library

[11]

Gianluca Dini and Angelica Lo Duca. 2012. A Secure Communication Suite for Underwater Acoustic Sensor Networks. MDPI Sensors 12(2012), 15133–15158. http://dx.doi.org/10.3390/s121115133

[12]

E. Dubrovinskaya, P. Casari, and R. Diamant. 2019. Bathymetry-aided Underwater Acoustic Localization using a Single Passive Receiver. J. Acoustic Soc. Am. 146, 6 (Dec. 2019), 4774–4789.

[13]

E. Dubrovinskaya, V. Kebkal, O. Kebkal, K. Kebkal, and P. Casari. 2020. Underwater Localization via Wideband Direction-of-Arrival Estimation Using Acoustic Arrays of Arbitrary Shape. Sensors, Special Issue “Internet of Underwater Things” 20, 14 (July 2020), 1–20.

[14]

Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016. Deep Learning. MIT Press, Cambridge, MA, USA. http://www.deeplearningbook.org.

Digital Library

[15]

X.C. Guo, J.H. Yang, C.G. Wu, C.Y. Wang, and Y.C. Liang. 2008. A novel LS-SVMs hyper-parameter selection based on particle swarm optimization. Neurocomputing 71, 16 (Oct. 2008), 3211–3215. https://www.sciencedirect.com/science/article/pii/S0925231208002932

Digital Library

[16]

Al Amin Islam and Kazi Abu Taher. 2021. A Novel Authentication Mechanism for Securing Underwater Wireless Sensors from Sybil Attack. In Proc. ICEEICT. IEEE, Mirpur, Dhaka, 1–6.

[17]

Shengming Jiang. 2019. On Securing Underwater Acoustic Networks: A Survey. IEEE Commun. Surveys Tuts. 21, 1 (2019), 729–752.

[18]

E. Jorswieck, S. Tomasin, and A. Sezgin. 2015. Broadcasting Into the Uncertainty: Authentication and Confidentiality by Physical-Layer Processing. Proc. IEEE 103, 10 (Oct. 2015), 1702–1724.

[19]

S. Kay. 1993. Fundamentals of Statistical Signal Processing: Estimation Theory. Prentice-Hall, Englewood Cliffs, NJ.

[20]

Muhammad Khalid, Ruiqin Zhao, and Nauman Ahmed. 2020. Physical Layer Authentication in Line-of-Sight Underwater Acoustic Sensor Networks. In Proc. MTS/IEEE OCEANS. IEEE, Singapore, 1–5.

[21]

C. Lal, R. Petroccia, K. Pelekanakis, M. Conti, and J. Alves. 2017. Toward the Development of Secure Underwater Acoustic Networks. IEEE J. Ocean. Eng. 42, 4 (Oct. 2017), 1075–1087.

[22]

A.J. Menezes, P.C. van Oorschot, and S.A. Vanstone. 1996. Handbook of Applied Cryptography. CRC Press, Boca Raton, FL.

[23]

Zoi-Heleni Michalopoulou, Peter Gerstoft, and Diego Caviedes-Nozal. 2021. Matched field source localization with Gaussian processes. JASA Express Lett. 1, 6 (2021).

[24]

Dalhatu Muhammed, Mohammad Hossein Anisi, Mahdi Zareei, and Anwar Khan. 2018. Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions. Sensors 18, 2 (Feb. 2018). art. 425.

[25]

K. Pelekanakis, C. M. G. Gussen, R. Petroccia, and J. Alves. 2019. Robust Channel Parameters for Crypto Key Generation in Underwater Acoustic Systems. In Proc. MTS/IEEE OCEANS. IEEE, Seattle, WA, USA, 1–7.

[26]

K. Pelekanakis, S.A. Yıldırım, G. Sklivanitis, R. Petroccia, J. Alves, and D. Pados. 2021. Physical Layer Security against an Informed Eavesdropper in Underwater Acoustic Channels: Feature Extraction and Quantization. In Proc. UCOMMS. IEEE, 1–5.

[27]

M. Porter 2018. Bellhop code. Retrieved Aug. 31, 2022 from http://oalib.hlsresearch.com/Rays/index.html

[28]

Manassés Ribeiro, André Eugênio Lazzaretti, and Heitor Silvério Lopes. 2018. A study of deep convolutional auto-encoders for anomaly detection in videos. Pattern Recognition Letters 105, C (apr 2018), 13–22.

[29]

Mohammad Sharif-Yazd, Mohammad Reza Khosrav, and Mohammad Kazem Moghimi. 2017. A Survey on Underwater Acoustic Sensor Networks: Perspectives on Protocol Design for Signaling, MAC and Routing. SciRP J. of Computer and Commun. 5, 5 (Feb. 2017), 12–23.

[30]

G. Sklivanitis, K. Pelekanakis, S.A. Yıldırım, R. Petroccia, J. Alves, and D. Pados. 2021. Physical Layer Security against an Informed Eavesdropper in Underwater Acoustic Channels: Reconciliation and Privacy Amplification. In Proc. UCOMMS. IEEE, 1–5.

[31]

Evaldo Souza, Hao Chi Wong, Italo Cunha, Ítalo Cunha, L. F. M. Vieira, and Leonardo B. Oliveira. 2013. End-to-end authentication in Under-Water Sensor Networks. In Proc. IEEE ISCC. IEEE, Split, Croatia, 299–304.

[32]

Harald Steck and Dario Garcia Garcia. 2021. On the Regularization of Autoencoders. https://arxiv.org/abs/2110.11402

[33]

M. Stojanovic and J. Preisig. 2009. Underwater acoustic communication channels: Propagation models and statistical characterization. IEEE Commun. Mag. 47, 1 (2009), 84–89.

Digital Library

[34]

Inam Ullah, Jingyi Chen, Xin Su, Christian Esposito, and Chang Choi. 2019. Localization and Detection of Targets in Underwater Wireless Sensor Using Distance and Angle Based Algorithms. IEEE Access 7(2019), 45693–45704.

[35]

Arjan Vermeij and Andrea Munafò. 2015. A Robust, Opportunistic Clock Synchronization Algorithm for Ad Hoc Underwater Acoustic Networks. IEEE J. Ocean. Eng. 40, 4 (2015), 841–852.

[36]

Chi Yuan, Wenping Chen, Yuqing Zhu, Deying Li, and Jie Tan. 2015. A Low Computational Complexity Authentication Scheme in Underwater Wireless Sensor Network. In Proc. MSN. IEEE, Shenzhen, China, 116–123.

Digital Library

[37]

O. Zeitouni, J. Ziv, and N. Merhav. 1992. When is the generalized likelihood ratio test optimal?IEEE Trans. Inf. Theory 38, 5 (1992), 1597–1602.

Digital Library

[38]

Shuailiang Zhang, Xiujuan Du, and Xin Liu. 2020. A Secure Remote Mutual Authentication Scheme Based on Chaotic Map for Underwater Acoustic Networks. IEEE Access 8(2020), 48285–48298.

[39]

Ruiqin Zhao, Muhammad Khalid, Octavia A. Dobre, and Xin Wang. 2022. Physical Layer Node Authentication in Underwater Acoustic Sensor Networks Using Time-Reversal. IEEE Sensors J. 22, 4 (2022), 3796–3809.

Cited By

Srinivasan MSenigagliesi LChen HChorti ABaldi MWymeersch H(2024)AoA-Based Physical Layer Authentication in Analog Arrays under Impersonation Attacks2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)10.1109/SPAWC60668.2024.10694672(496-500)Online publication date: 10-Sep-2024
https://doi.org/10.1109/SPAWC60668.2024.10694672
Adam NAli MNaeem FGhazy AKaddoum G(2024)State-of-the-Art Security Schemes for the Internet of Underwater Things: A Holistic SurveyIEEE Open Journal of the Communications Society10.1109/OJCOMS.2024.34742905(6561-6592)Online publication date: 2024
https://doi.org/10.1109/OJCOMS.2024.3474290
Eccher DCasari P(2024)Physical Layer Authentication via Underwater Acoustic Multipath Channel CraftingOCEANS 2024 - Halifax10.1109/OCEANS55160.2024.10753810(1-6)Online publication date: 23-Sep-2024
https://doi.org/10.1109/OCEANS55160.2024.10753810
Show More Cited By

Index Terms

Physical Layer Authentication in Underwater Acoustic Networks with Mobile Devices

Recommendations

An environment-friendly spectrum decision strategy for underwater acoustic networks

As the expansion of marine exploration, an increasing number of scholars have turned to the research of underwater acoustic networks (UANs). Recently, much attention was focused on enabling acoustic communication in UANs, a single network. However, in ...
A RNN-based approach to physical layer authentication in underwater acoustic networks with mobile devices
Abstract
Underwater acoustic communications are becoming a popular solution for underwater data communications and telemetry, making the authentication of transmitted data a necessity. In this paper, we propose a physical-layer authentication strategy for ...
Modem design for underwater acoustic networks: Taxonomy, capabilities, challenges, applications and future trends
Special section: Recent trends, Challenges and Applications in Cognitive Computing for Intelligent Systems

In underwater acoustic networks (UANs), an acoustic modem is one of the key elements that governs underwater communications. The major demerit of the existing surveys conducted on acoustic modems is that such surveys do not comprise of the novel and state-...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

WUWNet '22: Proceedings of the 16th International Conference on Underwater Networks & Systems

November 2022

190 pages

ISBN:9781450399524

DOI:10.1145/3567600

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 December 2022

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Funding Sources

North Atlantic Treaty Organization
Italian Ministry of Education

Conference

WUWNet'22

WUWNet'22: The 16th International Conference on Underwater Networks & Systems

November 14 - 16, 2022

MA, Boston, USA

Acceptance Rates

Overall Acceptance Rate 84 of 180 submissions, 47%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

7
Total Citations
View Citations
405
Total Downloads

Downloads (Last 12 months)217
Downloads (Last 6 weeks)34

Reflects downloads up to 18 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Srinivasan MSenigagliesi LChen HChorti ABaldi MWymeersch H(2024)AoA-Based Physical Layer Authentication in Analog Arrays under Impersonation Attacks2024 IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)10.1109/SPAWC60668.2024.10694672(496-500)Online publication date: 10-Sep-2024
https://doi.org/10.1109/SPAWC60668.2024.10694672
Adam NAli MNaeem FGhazy AKaddoum G(2024)State-of-the-Art Security Schemes for the Internet of Underwater Things: A Holistic SurveyIEEE Open Journal of the Communications Society10.1109/OJCOMS.2024.34742905(6561-6592)Online publication date: 2024
https://doi.org/10.1109/OJCOMS.2024.3474290
Eccher DCasari P(2024)Physical Layer Authentication via Underwater Acoustic Multipath Channel CraftingOCEANS 2024 - Halifax10.1109/OCEANS55160.2024.10753810(1-6)Online publication date: 23-Sep-2024
https://doi.org/10.1109/OCEANS55160.2024.10753810
Tomović SKrivokapić BNađ ÐRadusinović I(2024)BEKMP: A Blockchain-Enabled Key Management Protocol for Underwater Acoustic Sensor NetworksIEEE Access10.1109/ACCESS.2024.340589012(74108-74125)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3405890
Ardizzon FCasari PTomasin S(2024)A RNN-based approach to physical layer authentication in underwater acoustic networks with mobile devicesComputer Networks10.1016/j.comnet.2024.110311243(110311)Online publication date: Apr-2024
https://doi.org/10.1016/j.comnet.2024.110311
Fedorova TRyzhov VSafronov KSemenov NSulaiman S(2024)Energy-Efficient and Reliable Deployment Models for Hybrid Underwater Acoustic Sensor Networks with a Mobile GatewayJournal of Marine Science and Application10.1007/s11804-024-00444-z23:4(960-983)Online publication date: 8-Jul-2024
https://doi.org/10.1007/s11804-024-00444-z
Pham TSenigagliesi LBaldi MFettweis GChorti A(2023)Machine Learning-Based Robust Physical Layer Authentication Using Angle of Arrival EstimationGLOBECOM 2023 - 2023 IEEE Global Communications Conference10.1109/GLOBECOM54140.2023.10437915(13-18)Online publication date: 4-Dec-2023
https://doi.org/10.1109/GLOBECOM54140.2023.10437915

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents