Introduction Shippers may undeclare maritime dangerous goods as general cargo to avoid the preparation time, documentation burden, and freight premium associated with dangerous goods transportation, creating serious risks for vessel safety, port operations, and the marine environment. This paper examines whether blockchain-enabled documentation can mitigate such undeclaration by improving provenance information and shortening preparation and verification time in the dangerous goods channel. Methods We develop a game-theoretic model with one carrier and a continuum of heterogeneous shippers who differ in their marginal willingness to pay for service level, and in which the carrier endogenously sets the dangerous goods transportation price. We characterize the equilibrium declaration behavior under a benchmark scenario and under blockchain adoption, and extend the model to settings with carrier competition and enhanced detection. Results Undeclaration motives vary with the service environment: when dangerous goods service is relatively low, service-sensitive shippers undeclare to access the faster generalcargo channel; when service is sufficiently high, price-sensitive shippers undeclare to avoid the dangerous goods tariff. The carrier’s profit-maximizing price therefore does not generally coincide with the regulatory objective of zero undeclaration. Blockchain adoption introduces two opposing forces: a service-enhancement effect that encourages truthful declaration and a cost-escalation effect that raises the dangerous goods price. As a result, blockchain reduces undeclaration only when documentation-time savings dominate the price premium induced by adoption costs; when this condition fails, adoption may increase undeclaration and reduce compliant shipper surplus. Discussion Blockchain-enabled documentation is not a universal safety remedy. Its effect on undeclaration depends on the interaction between documentation-time savings and the adoption-driven price increase, and the extensions with carrier competition and enhanced detection show that blockchain deployment should be evaluated jointly with pricing, detection, competition, and regulatory policies.
Background: Maritime container shipping carries over 80% of global trade, yet compliance verification creates a confidentiality–verifiability conflict: carriers treat telemetry as commercially sensitive, while regulators, insurers, and port authorities require verifiable proof that cargo remained within specification. The EU Ecodesign for Sustainable Products Regulation (ESPR) mandates Digital Product Passports (DPPs), but no standardised DPP architecture exists for the multi-stakeholder maritime domain. Methods: We present Ocean DPP, a blockchain-anchored platform combining GS1 EPCIS 2.0, oneM2M, IOTA, and Groth16 zero-knowledge proofs (ZKPs), letting stakeholders verify compliance predicates without revealing raw sensor values; Merkle-tree batching reduces anchoring costs. We evaluate it in 16 experiments on a single-host testbed using synthetic workloads and a local IOTA network. Results: The platform achieved 95th-percentile latency of 48 ms without ZKP and 500 ms with proof generation, throughput of 7 events/s per host, 304 ms mean proof generation and 9.8 ms verification, 100% EPCIS 2.0 compliance, and zero permanent message loss across four failure-injection scenarios; horizontal scaling reduced the median latency by 37%. Conclusions: To the best of our knowledge, Ocean DPP is the first implemented, quantitatively evaluated platform integrating EPCIS 2.0, oneM2M, IOTA, and Groth16 ZKPs for privacy-preserving maritime DPPs; broader multi-host and public-network validation remains for future work.
Maritime shipping carries over 80% of global trade by volume, yet the information systems underpinning this vast network remain fragmented, proprietary, and mutually distrustful. This paper presents the Cascading Visibility Model (CVM), a theoretical framework formalizing how a single upstream data failure propagates non-linearly through carrier, port, customs, warehouse, and trucking handoffs. We introduce the Entropy Amplification Index (EAI) as a normalized measure of information loss per handoff layer, with estimated values exceeding 0.6 at the carrier-to-port boundary and approaching 0.8 at port-to-customs. We further characterize the Multi-Layer Trust Deficit as a maritime-specific prisoner's dilemma in which rational data hoarding by individual actors produces collectively catastrophic coordination failures. To address these failures, we propose the Distributed Vessel Trust Pool (DVTP), a protocol-layer architecture enabling multi-party vessel verification without requiring raw data disclosure. The DVTP uses physical impossibility detection anchored to third-party-generated port event timestamps that vessels cannot falsify, combined with zero-knowledge proof logic to trigger automatic cascade holds across interconnected ports. Three adversarial scenarios are analyzed theoretically. We compare the DVTP with the Portbase model and TradeLens failure to derive governance lessons. We also present a formal research agenda of eight hypotheses for empirical validation through discrete-event simulation. This paper is a theoretical framework and research agenda contribution. The EAI estimates presented are model-derived under stated assumptions; the DVTP architecture and its adversarial analysis are theoretical proposals; and the simulation design is specified for future execution.
Joel Curado Silveirinha, Manila Bhandari, João C. Ferreira, Ana Martins
Despite the maritime supply chain being the backbone of global trade, it faces persistent challenges in transparency, fraud prevention, shipment tracking and data privacy. Blockchain technology has emerged as a transformative solution, enhancing trust and traceability within supply chain networks. However, its limitations in data privacy and scalability necessitate advanced privacy-preserving mechanisms. Zero-Knowledge Proofs (ZKP) offers a cryptographic approach to validate data without exposing sensitive information, addressing blockchain’s privacy constraints. This paper reviews the state of the art on current applications of blockchain in maritime supply chain management and explores the integration of ZKP for secure trade document verification, fraud detection, privacy-preserving traceability and regulatory compliance. Additionally, it examines computational overhead, scalability and adoption barriers while proposing future research directions. Implementing ZKP within blockchain-based port operations enables robust governance models, ensuring data verification without revealing confidential details. This approach fosters a secure and privacy-compliant trade environment, enhancing trust and collaboration among stakeholders. By optimising resource allocation and mitigating risks, integrating ZKP can significantly improve maritime supply chain efficiency. Integrating Zero-Knowledge Proofs with blockchain, maritime logistics can achieve a balance between transparency, security and operational efficiency, addressing existing challenges in data privacy and regulatory compliance, improving the sustainability of port operations.
This study investigates the transformative potential of blockchain-enabled information systems for transparent greenhouse gas (GHG) reporting in maritime training organizations, addressing critical gaps in regulatory compliance and environmental accountability. Through qualitative thematic analysis of in-depth interviews with five maritime education professionals, this research examines how distributed ledger technology can revolutionize compliance with emerging EU regulations, including FuelEU Maritime directives and EU Emissions Trading System (ETS) requirements, alongside International Maritime Organization (IMO) standards. The study reveals that blockchain technology offers unprecedented solutions to longstanding challenges in maritime education systems, particularly in transparency, verification accuracy, and cross-organizational interoperability. Key findings highlight the technology's capacity to enable smart contract automation for real-time compliance monitoring, create immutable credentialing systems that enhance trust among stakeholders, and establish secure, tamper-proof records of seafarer competency development and environmental certification processes. Results demonstrate that blockchain-based systems can significantly strengthen the integrity of maritime training records while streamlining regulatory reporting processes.
Kemal Ihsan Kilic, Samir Maity, Inkyung Sung, Peter Nielsen
Maritime Search and Rescue (MSAR) operations face significant challenges due to high uncertainty, dynamic conditions, and resource constraints. Additionally, rigid organizational structures and hierarchical human-centered communication frameworks, fail to adapt to the challenging conditions of maritime environments. This paper provides a comprehensive review of the integration of Artificial Intelligence (AI) into MSAR operations, highlighting how AI can transform these systems through enhanced decision-making, real-time adaptability, decentralized autonomy, and resource optimization. Through analysis and synthesis, we identified and categorized key challenges in traditional SAR frameworks, such as inherent environmental and structural challenges. We discussed AI-driven solutions that offer efficient, autonomous, resilient, and decentralized coordination. Our thematic and statistical analysis of existing literature reveals significant research gaps, particularly regarding the holistic integration of AI across all SAR stages toward a decentralized fully autonomous paradigm shift. The paper also considers the technological challenges for the integration and adaptation of AI in SAR. By envisioning fully autonomous, AI-driven MSAR operations, this study sets the stage for future research and practical innovations, aiming to improve effectiveness and efficiency in maritime rescue efforts. • Comprehensive Literature Review of AI over MSAR. • Identification of Gaps and Key Challenges in MSAR. • Proposed AI-Driven Solutions Strategies for MSAR. • Trends and Future Directions through AI in MSAR.
Although modern Maritime Transportation Systems (MTS) have been extensively benefited from Internet of Things (IoT) technology, but still the risks and challenges in safety and reliability have increased substantially. The involvement of different maritime parties in the marine transportation flow scheduling and management further escalates these challenges. Thus, we need an IoT-based collaborative processing system that unifies the modular structure and integrates multiple modules involved in MTS. Moreover, the need for a shared and controlled access mechanism that cannot be manipulated or tampered by unauthorized parties is also essential requirement in MTS. Blockchain, as an emerging technology, has become a key tool in data security protection because of its non-tampering and non-forgery characteristics. Keeping in view of this aspect, in this paper, an IoT-based collaborative processing system based on blockchain is proposed for marine transportation flow scheduling and management. In addition, we propose a novel consensus mechanism based on Verifiable Random Function (VRF) and reputation voting to reduce the communication cost in blockchain consensus communication process. The proposed scheme has been validated in a simulated environment and the results illustrate that the scheme has obvious effect in resisting replay attack and camouflage attack. Furthermore, the optimized consensus mechanism improves the security by 8% and the transaction processing speed by 6% on the premise that the communication cost is basically unchanged.
This paper proposes a blockchain-based framework to improve the efficiency of ship traffic in port. In the framework, ship agents, terminals, tug company, pilot station, and government share information and the information is stored in a blockchain. Based on the shared information, we discuss three categories of data-driven models that can improve the operations management of the above five parties. The first category is decisions made by a single party. The second category involves decisions of at least two ship agents. The third category relates to multi-party decision-making under uncertainty. This study hopes to stimulate maritime practitioners to embrace blockchain technology and data-driven approaches to enhance the competitiveness of the industry.
Autonomous ships are in experimental stage nowadays with Maritime Autonomous Surface Ships (MASS) already defined by IMO. Since MASS rely heavily on communications, security of communication systems and data security is critical. Secure communication is required to avoid bad actors to interfere with the communications or seizing control of a autonomous ship. In this paper, implementation of blockchain technology to improve autonomous vessels control security is investigated. This technology is already used in maritime bill of lading, acts on ship's technical inspection and for more accurate container tracking etc. The paper is organized as follows: first section describes current status on autonomous ships, basic definitions and terms, second section describes what is blockchain technology and how does it work, third section deals with blockchain technology applications with the proposed usage of the technology in autonomous vessels control scheme.