Decoding dependencies among the risk factors influencing maritime cybersecurity: Lessons learned from historical incidents in the past two decades

Ocean Engineering, Journal Year: 2024, Volume and Issue: 312, P. 119078 - 119078

Published: Aug. 29, 2024

The distinctive features of maritime infrastructures present significant challenges in terms security.Disruptions to the normal functioning any part transportation can have wide-ranging consequences at both national and international levels, making it an attractive target for malicious attacks.Within this context, integration digitalization technological advancements seaports, vessels other elements exposes them cyber threats.In response critical challenge, paper aims formulate a novel cybersecurity risk analysis method ensuring security.This approach is based on data-driven Bayesian network, utilizing recorded incidents spanning past two decades.The findings contribute identification highly contributing factors, meticulous examination their nature, revelation interdependencies, estimation probabilities occurrence.Rigorous validation developed model ensures its robustness diagnostic prognostic purposes.The implications drawn from study offer valuable insights stakeholders governmental bodies, enhancing understanding how address threats affecting industry.This knowledge aids implementation necessary preventive measures.

Language: Английский

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Enhancing maritime transportation security: A data‐driven Bayesian network analysis of terrorist attack risks

Risk Analysis, Journal Year: 2024, Volume and Issue: 45(2), P. 283 - 306

Published: July 21, 2024

Maritime terrorist accidents have a significant low-frequency-high-consequence feature and, thus, require new research to address the associated inherent uncertainty and scarce literature in field. This article aims develop novel method for maritime security risk analysis. It employs real accident data from attacks over past two decades train data-driven Bayesian network (DDBN) model. The findings help pinpoint key contributing factors, scrutinize their interdependencies, ascertain probability of different scenarios, describe impact on manifestations terrorism. established DDBN model undergoes thorough verification validation process employing various techniques, such as sensitivity, metrics, comparative analyses. Additionally, it is tested against recent real-world cases demonstrate its effectiveness both retrospective prospective propagation, encompassing diagnostic predictive capabilities. These provide valuable insights stakeholders, including companies government bodies, fostering comprehension terrorism potentially fortifying preventive measures emergency management.

Language: Английский

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Resilience analysis of seaports: a critical review of development and research directions

Maritime Policy & Management, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 36

Published: March 23, 2025

Language: Английский

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Prioritizing Factors Influencing Global Network Readiness Index with Bayesian Belief Networks

Journal of Open Innovation Technology Market and Complexity, Journal Year: 2025, Volume and Issue: unknown, P. 100522 - 100522

Published: March 1, 2025

Language: Английский

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Shifting landscape of terrorism: A 50‐year spatiotemporal analysis

Risk Analysis, Journal Year: 2025, Volume and Issue: unknown

Published: March 30, 2025

Abstract This study aims to analyze the spatiotemporal evolutionary characteristics of global terrorism from 1970 2020, providing a comprehensive understanding its dynamics and patterns. The research seeks fill gaps in existing literature by integrating geographic perspectives methods enhance terrorism's spatial temporal dimensions. employs multi‐methodological approach, combining Mann–Kendall trend test, autocorrelation analysis, kernel density estimation, standard deviational ellipse. These are applied data 176 countries, covering 171,327 terrorist incidents recorded Global Terrorism Database (GTD) 2020. Pertinent findings as follows. Temporally, risk has evolved significantly over past five decades involves four distinct stages, i.e., emerging stage (1970–1991), descending (1992–2000), rampant (2001–2014), attenuating (2015–2020). Meanwhile, 117 countries show an increasing trend, 56 decreasing risk. Spatially, distribution is characterized clustering aggregation, with constant shift gravity center dominant direction. In addition, hotspots predominantly presented “two major core circles multiple sub‐centers.”

Language: Английский

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Maritime security threats: Classifying and associating patterns in piracy and armed robbery incidents

Ocean & Coastal Management, Journal Year: 2025, Volume and Issue: 266, P. 107685 - 107685

Published: April 15, 2025

Language: Английский

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Analysis of the impact of climate-driven Extreme Weather Events (EWEs) on the UK train delays: A data-driven BN approach

Reliability Engineering & System Safety, Journal Year: 2025, Volume and Issue: 262, P. 111189 - 111189

Published: April 25, 2025

Language: Английский

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Dynamic Bayesian Networks, Elicitation, and Data Embedding for Secure Environments

Entropy, Journal Year: 2024, Volume and Issue: 26(11), P. 985 - 985

Published: Nov. 17, 2024

Serious crime modelling typically needs to be undertaken securely behind a firewall where police knowledge and capabilities remain undisclosed. Data informing an ongoing incident are often sparse; large proportion of relevant data only come light after the culminates or intervene-by which point it is too late make use aid real-time decision-making for in question. Much that

Language: Английский

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