Abstract
As maritime and military missions become more and more complex over the years, there has been a high interest in the research and development of Unmanned Underwater Vehicles (UUVs). Latest efforts concern the modeling and simulation of UUVs collaboration within formations of vehicles (swarms), towards obtaining deeper insights related to critical issues related to cybersecurity and interoperability. The research issues which are constantly emerging in this domain are closely related to the communication, interoperability, and secure operation of trustworthy UUVs, as well as to the volume, velocity, variety, and veracity of data transmitted in low bitrate due to the medium i.e., the water. This paper focuses on such issues in the domain of UUVs, emphasizing interoperability and cybersecurity in swarms of trustworthy UUVs in a military/search-and-rescue (SAR) setting. The aim of this paper is to present preliminary work on a semantic modeling and simulation approach that aims to facilitate commanders of military/search-and-rescue operations to effectively support critical and life-saving decision-making, while handling interoperability and cybersecurity issues on the Internet of Underwater Things (IoUT).
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References
Aggarwal, P., Gonzalez, C., Dutt, V.: HackIt: a real-time simulation tool for studying real-world cyberattacks in the laboratory. In: Gupta, B.B., Perez, G.M., Agrawal, D.P., Gupta, D. (eds.) Handbook of Computer Networks and Cyber Security, pp. 949–959. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-22277-2_39
Ahmad, I., et al.: Analysis of security attacks and taxonomy in underwater wireless sensor networks. Wirel. Commun. Mob. Comput. 2021 (2021). https://doi.org/10.1155/2021/1444024
Bagyalakshmi, G., et al.: Network vulnerability analysis on brain signal/image databases using Nmap and Wireshark tools. IEEE Access 6, 57144–57151 (2018). https://doi.org/10.1109/ACCESS.2018.2872775
Barbie, A., et al.: Developing an underwater network of ocean observation systems with digital twin prototypes - a field report from Baltic sea. IEEE Internet Comput. (2021). https://doi.org/10.1109/MIC.2021.3065245
Bhattacharjya, K., De, D.: IoUT: modelling and simulation of edge-drone-based software-defined smart internet of underwater things. Simul. Model. Pract. Theory 109, 102304 (2021). https://doi.org/10.1016/j.simpat.2021.102304
Bouter, C., Kruiger, H., Verhoosel, J.: Domain-Independent Data Processing in an Ontology Based Data Access Environment Using the SOSA Ontology (2021). http://ceur-ws.org
Caldera Description page. https://www.pwc.co.uk/issues/imitation-game-attacker-emulation.html. Accessed 06 Mar 2022
Centelles, D., Soriano-Asensi, A., Martí, J.V., Marín, R., Sanz, P.J.: Underwater wireless communications for cooperative robotics with UWSim-NET. Appl. Sci. 9(17), 3526 (2019). https://doi.org/10.3390/app9173526
Chhokra, A., Barreto, C., Dubey, A., Karsai, G., Koutsoukos, X.: Power-attack: a comprehensive tool-chain for modeling and simulating attacks in power systems (n.d.)
Cornejo-Lupa, M.A., Cardinale, Y., Ticona-Herrera, R., Barrios-Aranibar, D., Andrade, M., Diaz-Amado, J.: OntoSLAM: an ontology for representing location and simultaneous mapping information for autonomous robots. Robotics 10(4), 125 (2021). https://doi.org/10.3390/robotics10040125
Domingo, M.C.: An overview of the internet of underwater things. J. Netw. Comput. Appl. 35(6), 1879–1890 (2012). https://doi.org/10.1016/j.jnca.2012.07.012
Fattah, S., Gani, A., Ahmedy, I., Idris, M.Y.I., Hashem, I.A.T.: A survey on underwater wireless sensor networks: requirements, taxonomy, recent advances, and open research challenges. Sensors 20(18), 1–30 (2020). https://doi.org/10.3390/s20185393
Gazebo Github page. https://github.com/osrf/gazebo. Accessed 06 Mar 2022
Gazebo Homepage. http://gazebosim.org/. Accessed 06 Mar 2022
Infection Monkey. https://github.com/guardicore/monkey. Accessed 06 Mar 2022
Braga, J., Martins, R., Petrioli, C., Petroccia, R., Picari, L.: Cooperation and networking in an underwater network composed by heterogeneous assets. In: OCEANS 2016 MTS/IEEE Monterey, pp. 1–9 (2016). https://doi.org/10.1109/OCEANS.2016.7761219
Janowicz, K., Haller, A., Cox, S.J.D., le Phuoc, D., Lefrançois, M.: SOSA: a lightweight ontology for sensors, observations, samples, and actuators. J. Web Semant. 56, 1–10 (2019). https://doi.org/10.1016/j.websem.2018.06.003
Jurasky, W., Moder, P., Milde, M., Ehm, H., Reinhart, G.: Transformation of semantic knowledge into simulation-based decision support. Robot. Comput.-Integr. Manuf. 71, 102174 (2021). https://doi.org/10.1016/j.rcim.2021.102174
Kamoun-Abid, F., Rekik, M., Meddeb-Makhlouf, A., Zarai, F.: Secure architecture for Cloud/Fog computing based on firewalls and controllers. Procedia Comput. Sci. 192, 822–833 (2021). https://doi.org/10.1016/j.procs.2021.08.085
Kutzke, D.T., Carter, J.B., Hartman, B.T.: Subsystem selection for digital twin development: a case study on an unmanned underwater vehicle. Ocean Eng. 223, 108629 (2021). https://doi.org/10.1016/j.oceaneng.2021.108629
LHN Infection Monkey page. https://latesthackingnews.com/2022/02/24/__trashed-4/. Accessed 06 Mar 2022
LinkedIn page. https://www.linkedin.com/pulse/auv-deepwater-search-rescue-arnt-helge-olsen/. Accessed 06 Mar 2022
Madan, B.B., Banik, M., Bein, D.: Securing unmanned autonomous systems from cyber threats. J. Defense Model. Simul. 16(2), 119–136 (2019). https://doi.org/10.1177/1548512916628335
Mary, D.R.K., Ko, E., Kim, S.-G., Yum, S.-H., Shin, S.-Y., Park, S.-H.: A systematic review on recent trends, challenges, privacy and security issues of underwater internet of things. Sensors 21(24), 8262 (2021). https://doi.org/10.3390/s21248262
Menaka, D., Gauni, S., Manimegalai, C.T., Kalimuthu, K.: Vision of IoUT: advances and future trends in optical wireless communication. J. Opt. 50 (n.d.). https://doi.org/10.1007/s12596
Migueláñez, E., Patrón, P., Brown, K.E., Petillot, Y.R., Lane, D.M.: Semantic knowledge-based framework to improve the situation awareness of autonomous underwater vehicles. IEEE Trans. Knowl. Data Eng. 23(5), 759–773 (2011). https://doi.org/10.1109/TKDE.2010.46
MITRE ATT&CK Description page for Caldera. https://www.mitre.org/research/technology-transfer/open-source-software/caldera%E2%84%A2. Accessed 06 Mar 2022
MITRE ATT&CK Homepage. https://attack.mitre.org/. Accessed 06 Mar 2022
Nayyar, A., Balas, V.E.: Analysis of simulation tools for underwater sensor networks (UWSNs). In: Bhattacharyya, S., Hassanien, A.E., Gupta, D., Khanna, A., Pan, I. (eds.) International Conference on Innovative Computing and Communications. LNNS, vol. 55, pp. 165–180. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-2324-9_17
NS-3 Introduction page. https://www.nsnam.org/docs/release/3.21/tutorial/ html/introduction.html. Accessed 06 Mar 2022
Oceanic Engineering Society (U.S.): Autonomous Underwater Vehicles 2016: AUV 2016: 6–9 November 2016, IIS, the University of Tokyo, Tokyo, Japan (n.d.)
Potter, J., Alves, J., Green, D., Zappa, G., McCoy, K., Nissen, I.: The JANUS underwater communications standard. In: 2014 Underwater Communications and Networking, UComms 2014 (2014). https://doi.org/10.1109/UComms.2014.7017134
Prats, M., Perez, J., Fernandez, J.J., Sanz, P.J.: An open-source tool for simulation and supervision of underwater intervention missions. In: IEEE International Conference on Intelligent Robots and Systems, pp. 2577–2582 (2012). https://doi.org/10.1109/IROS.2012.6385788
Public Affairs Office: NATO STO-CMRE Science and Technology Organization Centre for Maritime Research and Experimentation (2020)
Syed, R.: Cybersecurity vulnerability management: a conceptual ontology and cyber intelligence alert system. Inf. Manag. 57(6), 103334 (2020). https://doi.org/10.1016/j.im.2020.103334
Syed, Z., Padia, A., Finin, T., Mathews, L., Joshi, A.: UCO: A Unified Cybersecurity Ontology (n.d.). http://tinyurl.com/ptqkzpq
Velu, A., Thangavelu, M.: Ontology based ocean knowledge representation for semantic information retrieval. Comput. Mater. Contin. 70(3), 4707–4724 (2022). https://doi.org/10.32604/cmc.2022.020095
Wikipedia page. https://en.wikipedia.org/wiki/Air_France_Flight_447#Underwater_search. Accessed 06 Mar 2022
Wikipedia page for ARP spoofing. https://en.wikipedia.org/wiki/ARP_spoofing. Accessed 06 Mar 2022
Wireshark Home page. https://www.wireshark.org/docs/. Accessed 06 Mar 2022
Wu, J., Yang, Y., Cheng, X.U.N., Zuo, H., Cheng, Z.: The development of digital twin technology review. In: Proceedings - 2020 Chinese Automation Congress, CAC 2020, pp. 4901–4906 (2020). https://doi.org/10.1109/CAC51589.2020.9327756.
Zachila, K., Kotis, K., Paparidis, E., Ladikou, S., Spiliotopoulos, D.: Facilitating semantic interoperability of trustworthy IoT entities in cultural spaces: the smart museum ontology. IoT 2(4), 741–760 (2021). https://doi.org/10.3390/iot2040037
Zhao, Y., Wang, Y., Zhang, H., Zhang, C., Yang, C.: Agent-based Network Security Simulator Nessi2 (2015)
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Stavrinos, S., Kotis, K., Kalloniatis, C. (2022). Towards Semantic Modeling and Simulation of Cybersecurity on the Internet of Underwater Things. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 646. Springer, Cham. https://doi.org/10.1007/978-3-031-08333-4_12
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