Building a virtual maritime logistics cybersecurity training platform

Harri Pyykkö, Jarkko Kuusijärvi, Sami Noponen, Sirra Toivonen and Ville Hinkka

A chapter in Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain, 2020, pp 223-246 from Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management

Abstract: Purpose: This paper proposes how cyber ranges, which are simulation environments and platforms, can be used for cybersecurity training to reduce the vulnerability surface of the maritime supply chain caused by cyberthreat challenges. An additional benefit to conducting exercises for personnel with realistic environments is that unseen problems can be detected when training with different scenarios. Methodology: This study aims to create a holistic model for a cyber range training environment customized for the port/maritime logistics sector by simulating the actual operational environment. The research combines cybersecurity and risk management with the special requirements of maritime logistics. The methods used were a literature review and a workshop and interview setup with cybersecurity, risk management and maritime professionals. Findings: The demand for high-level resilience in global maritime supply chains, in addition to better business continuity management, is becoming increasingly important as global markets seek rapid responses to change. There are various new emerging technologies in the pipeline, which are rapidly gaining popularity in the logistics and supply chain management context. Cybersecurity preparedness is therefore essential. Originality: Organizational and individual cybersecurity preparedness can be improved when individuals have access to hands-on training with realistic cyber exer-cise scenarios that cover different levels of interactions and triggers/injects in the actual environment. The training scheme focuses on training both technical and non-technical staff to provide extensive coverage of cyber awareness.

Keywords: Logistics; Industry 4.0; Digitalization; Innovation; Supply Chain Management; Artificial Intelligence; Data Science (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:hiclch:228922

DOI: 10.15480/882.3130

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