Applications of AI /ML in Maritime Cyber Supply Chains

被引:1
|
作者
Diaz, Rafael [1 ]
Ungo, Ricardo [1 ]
Smith, Katie [2 ]
Haghnegahdar, Lida [1 ]
Singh, Bikash [1 ]
Phuong, Tran [1 ]
机构
[1] Old Dominion Univ, Sch Cybersecur, Interdisciplinary Studies, Norfolk, VA 23529 USA
[2] Old Dominion Univ, Virginia Modeling Anal & Simulat Ctr, Norfolk, VA USA
来源
5TH INTERNATIONAL CONFERENCE ON INDUSTRY 4.0 AND SMART MANUFACTURING, ISM 2023 | 2024年 / 232卷
关键词
Supply Chain Cybersecurity; Maritime and Shipbuilding; Artificial Intelligence; Machine Learning; FRAMEWORK;
D O I
10.1016/j.procs.2024.02.140
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Digital transformation is a new trend that describes enterprise efforts in transitioning manual and likely outdated processes and activities to digital formats dominated by the extensive use of Industry 4.0 elements, including the pervasive use of cyber-physical systems to increase efficiency, reduce waste, and increase responsiveness. A new domain that intersects supply chain management and cybersecurity emerges as many processes as possible of the enterprise require the convergence and synchronizing of resources and information flows in data-driven environments to support planning and execution activities. Protecting the information becomes imperative as big data flows must be parsed and translated into actions requiring speed and accuracy. Machine learning and artificial intelligence have become critical in supporting extensive data collection and real-time processing to assist decision-makers in configuring scarce resources. In this paper, we present four different applications that investigate issues related to the broader maritime supply chain security domain affecting the planning, execution, and performance of complex systems while exploring novel frontiers in cyber research and education. This paper will focus on Machine Learning and AI applications on Unmanned Aerial Systems and Cryptography related to Cybersecurity in Maritimes and Shipbuilding Spheres. (c) 2023 The Authors. Published by ELSEVIER B.V.
引用
收藏
页码:3247 / 3257
页数:11
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