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Towards The Creation of A Threat Intelligence Framework for Maritime Infrastructures

Pitropakis, Nick; Logothetis, Marios; Andrienko, Gennady; Karapistoli, Irene; Stephanatos, Jason; Lambrinoudakis, Costas

Authors

Marios Logothetis

Gennady Andrienko

Irene Karapistoli

Jason Stephanatos

Costas Lambrinoudakis



Abstract

The maritime ecosystem has undergone through changes due to the increasing use of information systems and smart devices. The newly introduced technologies give rise to new attack surface in maritime infrastructures. In this position paper, we propose the MAritime Threat INtelligence FRAMEwork (MAINFRAME), which is tailored towards collection and analysis of threat intelligence in maritime environments. MAINFRAME combines: (i) data collection from ship sensors; (ii) collection of publicly available data from social media; (iii) variety of honeypots emulating different hardware and software component; (iv) event detection assisted by deep learning; (v) blockchain implementation that maintains audit trail for activities and transactions, and electronic IDs; and (vi) visual threat analytics. To highlight the interdependencies between cyber and cyber-physical threats in autonomous ships, MAIN-FRAME's operation is evaluated through the liquefied natural gas (LNG) Carrier case study.

Presentation Conference Type Conference Paper (Published)
Conference Name 5th Workshop on the Security of Industrial Control Systems & of Cyber-Physical Systems (CyberICPS 2019)
Start Date Sep 23, 2019
End Date Sep 27, 2019
Acceptance Date Aug 9, 2019
Online Publication Date Feb 22, 2020
Publication Date 2020
Deposit Date Jan 30, 2020
Publisher Springer
Pages 53-68
Series Title Lecture Notes in Computer Science
Series Number 11980
Series ISSN 0302-9743
Book Title Computer Security: ESORICS 2019 International Workshops, CyberICPS, SECPRE, SPOSE, and ADIoT
ISBN 978-3-030-42047-5
DOI https://doi.org/10.1007/978-3-030-42048-2_4
Keywords Maritime, Cybersecurity, Threat Intelligence
Public URL http://researchrepository.napier.ac.uk/Output/1733052