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.
Carolina Gonzalez Cambero, PAULA LAMO ANUARBE, Javier Rainer Granados
The digital transformation of the insurance sector is advancing through hybrid architectures that integrate distributed ledgers, the Internet of Things (IoT), and artificial intelligence (AI). This paper proposes a hybrid IoT–DLT architecture for parametric insurance systems operating in environments with variable connectivity. The architecture is designed to ensure data verifiability, operational resilience, and regulatory compliance with the General Data Protection Regulation (GDPR) and the Digital Operational Resilience Act (DORA). The approach is validated through a maritime cold-chain monitoring use case for fishing fleets, based on onboard IoT sensors and smart contracts. Simulation results show that the proposed multi-sensor consensus mechanism enables accurate detection of thermal breaches while significantly reducing the number of blockchain transactions by reserving on-chain registration for critical events only. The proposed approach supports distributed, auditable, and operational insurance systems even under intermittent connectivity conditions. Keywords: hybrid architecture, blockchain, Internet of Things, artificial intelligence, parametric insurance.
В статье рассматривается концепция применения роевого интеллекта и эмерджентных свойств распределённых систем автономных необитаемых подводных аппаратов в задачах подводной логистики. Показано, что переход от одиночных аппаратов и централизованных схем управления к децентрализованным роевым системам позволяет сформировать качественно новые свойства транспортных систем, включая повышенную энергетическую эффективность, отказоустойчивость и адаптивность к изменяющимся условиям подводной среды. На основе положений теории сложных систем и синергетики проанализированы механизмы самоорганизации и коллективного поведения АНПА, приводящие к возникновению эмерджентных эффектов на уровне транспортной системы. Предложена классификация эмерджентных эффектов, имеющих практическое значение для подводной транспортировки грузов, а также рассмотрены синергетические механизмы, обеспечивающие снижение удельных энергозатрат при коллективном движении аппаратов. Обсуждаются перспективы практического применения роевых систем АНПА в подводной логистике, включая контейнерные перевозки и транспортировку экологически чувствительных грузов, а также ограничения и направления дальнейших исследований. The paper examines the application of swarm intelligence and emergent properties of distributed autonomous underwater vehicle (AUV) systems to underwater logistics tasks. It is shown that the transition from single-vehicle and centralized control architectures to decentralized swarm-based systems enables the formation of qualitatively new transport system properties, including increased energy efficiency, fault tolerance, and adaptability to changing underwater environmental conditions. Based on concepts from complex systems theory and synergetic, the mechanisms of self-organization and collective behavior of AUV swarms leading to the emergence of system-level effects are analyzed. A classification of emergent effects that are practically significant for underwater cargo transportation is proposed, and synergistic mechanisms responsible for the reduction of specific energy consumption during collective vehicle motion are discussed. The prospects for practical implementation of swarm-based AUV systems in underwater logistics, including container transportation and the handling of environmentally sensitive cargoes, are considered, along with the limitations of the proposed approach and directions for further research.
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.
Yi Yang, Debiao He, Pandi Vijayakumar, Brij B. Gupta · 5 authors
Maritime transportation has ushered in a period of vigorous development and has been the most critical mode of transport in international trade. Maritime communication is also becoming increasingly complex. This trend needs the IoT-enabled Maritime Transportation System (IMTS) to enhance its ability of privacy-preserving, performance continuously, and add the function of joint management. Although many aggregate signcryption (ASC) schemes have been presented to satisfy this requirement, they still suffer from performance deficiencies or security weaknesses. To address these issues, we design a more practical “Perception-Network-Application” IoT-enabled MTS (PNA-IMTS) network structure. Then, we propose an efficient Identity-based aggregate signcryption scheme with blockchain (B-ID-ASC) for PNA-IMTS based on this network model. The security analysis shows that the B-ID-ASC scheme is capable of providing confidentiality and unforgeability. It also can resist existing known attacks (impersonation attack, modification attack, man-in-the-middle attack). The performance analysis indicates that our B-ID-ASC scheme, having lower computation and communication costs than current ASC schemes, is more applicable for PNA-IMTS.
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.
Ambigavathi Munusamy, Mainak Adhikari, Mohammad Ayoub Khan, Varun G. Menon · 7 authors
With the exponential growth of the Internet of Things (IoT) devices in Maritime Transportation Systems (MTS), the centralized cloud-centric framework can hardly meet the requirements of the applications in terms of low latency and power consumption. By inventing the distributed edge-centric framework, real-time IoT applications can meet the requirements of the MTS by analyzing the tasks at the edge of the networks. However, one of the critical challenges of the edge-centric MTS is to provide security and privacy between local IoT devices and distributed edge nodes. Motivated by that, in this paper, we design a blockchain-enabled edge-centric framework for analyzing the real-time data at the edge of the networks with minimum latency and power consumption while meeting the security and privacy issue of MTS. The introduction of blockchain and smart contract in the edge-centric MTS frameworks help to validate the transactions of each block at edge nodes by estimating the lifetime, belief, and trustfulness, and mitigate various types of security threats. Further, we introduce different classification models to predict the malicious vessels over the real-time maritime dataset at a secured edge-centric MTS framework. Extensive simulation results demonstrate that the superiority of the proposed strategy with baseline approaches under various performance metrics.
Chen Wang, Jian Shen, Pandi Vijayakumar, Brij B. Gupta
With global economic integration, transnational trade plays an important role, and maritime transportation is one of the important means of freight transportation. It is of great significance to build a secure and efficient maritime transportation system (MTS). The introduction of Internet of things technology makes MTS more perfect. The IoT-enabled MTS is composed of marine terminals and on-board sensors, land-based data centers and base stations, as well as satellite networks. Many researchers have carried out significant work to aggregate data in MTS. However, because the terrestrial base stations cannot cover most of the sea area, the isolated maritime terminals, those who drive to the area without base station coverage, need the assistance of satellite networks to complete the contact with the data center. In this paper, we propose an attribute based secure data aggregation scheme for isolated IoT-enabled MTS. In the novel scheme, the constant attributes of a maritime terminal are utilized to generate its certification. In addition, on-board sensors are introduced in the system to help aggregate the status and surrounding environment of the maritime terminal. These monitoring data are encrypted by the sensors and transmitted to the data center for the trustworthiness evaluation of the isolated maritime terminal. Besides, the zero-knowledge proof is utilized to confirm the legitimacy of participating users. What's more, the security analysis and the simulation results show that the novel scheme is secure and efficient for IoT-enabled MTS.
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.