Decentralized unmanned aerial vehicle (UAV) swarms require low-latency peer communication while remaining resilient to spoofing, replay, command injection, key compromise, and malicious membership changes. This study develops a zero-trust communication framework that separates the real-time swarm data plane from a permissioned Byzantine-fault-tolerant trust ledger. The method is grounded in an existing GPS-denied UAV software baseline implementing canonical packet hashing, HMAC-SHA256 authentication, trust epochs, timestamp and sequence freshness checks, onboard security-state transitions, command-policy gating, and firmware trust records. The proposed extension introduces per-node identities, authenticated session establishment, AEAD-protected peer traffic, and event-sparse ledger anchoring for trust-changing evidence. Formal models are derived for message acceptance, trust dynamics, Byzantine tolerance, consensus traffic, storage growth, processing overhead, and energy cost. Under a representative analytical case of 100 swarm messages/s, a 1% anchoring ratio reduces ledger event rate and modeled consensus-control traffic by 100 times compared with per-packet anchoring. Repository benchmark measurements are reported separately from blockchain projections. The analysis supports using blockchain as a decentralized trust anchor rather than as a transport for flight-critical telemetry.
The integration of real-time capacity optimization suites within legacy civil aviation computing ecosystems is highly bottlenecked by the severe structural heterogeneity of distribution data infrastructures. Telemetry and transactional feeds remain highly siloed across disparate legacy Global Distribution System (GDS) alphabetic fields, Low-Cost Carrier (LCC) direct APIs, and non-public multi-alliance loyalty program ledger inventories. This paper presents a sovereign computational architecture engineered to achieve distributed eventual consistency across these fragmented environments. The system introduces an automated Heterogeneous Data Fusion (H-Pipeline) layer that aggregates high-frequency multi-source distribution data streams into a unified, encrypted semantic vector space through specialized vector dimension coalescing protocols operating under strict TLS 1.3 mutual authentication frameworks. To intelligently parse and navigate these multi-source streams, the architecture deploys an asynchronous, cloud-native Large Language Model (LLM) orchestration middleware running entirely within serverless stateless edge containers (AWS Wavelength/Cloudflare Workers meshes). The cloud-native LLM layer is established as an asynchronous predictive semantic router, dynamically identifying macroeconomic anomalies, unexpected capacity imbalances, and transient route volatility without introducing synchronized write-back overhead or data persistence bottlenecks to critical On-Line Transaction Processing (OLTP) reservation threads. Simulation-based performance evaluation utilizing industry-standard benchmark datasets confirms single-digit millisecond failover recovery bounds, a strict 12 ms cross-border fiber pathway propagation convergence limit, and total mitigation of cross-region distributed semantic drift, establishing a robust computational foundation for next-generation asynchronous AI airline operations.
Aircraft maintenance records are critical to airworthiness and asset valuation, yet they are often fragmented across stakeholders, creating verification bottlenecks and information asymmetry that may suppress aircraft residual value. This paper proposes a blockchain-anchored decentralized application (dApp) based on a dual-layer architecture that combines InterPlanetary File System (IPFS)-based off-chain storage with on-chain anchoring of Content Identifiers (CIDs) and selected metadata. With respect to off-chain file size, the on-chain payload per record remains $\mathcal{O}(1)$, compared with $\mathcal{O}(n)$ for direct on-chain file storage. The architecture incorporates metadata and traceability controls informed by Federal Aviation Administration (FAA) electronic recordkeeping guidance. The main contribution is an economic framework that models the relationship between tamper-evident maintenance-record provenance, audit workflow duration, aircraft residual value, and operational cost. In a 7-kB experiment conducted on the BNB Smart Chain testnet, CID anchoring reduced gas consumption by 93.9\% compared with direct on-chain storage. Under explicitly stated scenario assumptions, the audit-cost model indicates potential savings of more than 90\%. These results support the technical feasibility of the prototype and illustrate its economic potential, while the estimated financial benefits remain to be validated using operational data.
A privacy-preserving compliance audit architecture for unmanned aerial vehicle (UAV) swarm operations. The central contribution is a deconfliction-to-containment reduction: rather than comparing n trajectories after the fact (a quadratic, disclosure-bound check), a planner assigns pairwise-disjoint spatial tubes before take-off and establishes their separation once, so that each vehicle subsequently attests only that its own samples stayed inside its own tube. Collision-freedom follows as a consequence (Theorem 2), and the pairwise cost is paid a single time at planning. The commitment layer (Layer 1) is implemented and evaluated as a decision-support audit pipeline that produces non-disclosing, tamper-evident audit artifacts via pre-flight Merkle commitments. It is evaluated in an emulated UAV swarm environment with systematic adversarial injection, in configurations up to 200 vehicles × 500 samples (100,000 sample statements), reporting artifact size, commit/prove/verify/disjunction times, and tamper-detection rates. We then formally identify the security boundary of the implemented layer: it provides coordinate hiding and tamper evidence, but cannot by itself make self-reported containment truthful, which we state as a security game and an impossibility result (Theorem 3). We specify the additional soundness layers (range proof, continuity, provenance and freshness, and aggregation) needed for full containment assurance, proving that composing a knowledge-sound range argument closes the gap (Theorem 4). Throughout, we separate the implemented and measured Layer 1 from the specified and proved—but not yet benchmarked—Layers 2–4, and we make no claim of full zero-knowledge geofence compliance, of swarm-scale deployment, or of deployment readiness.
The aviation industry depends on data integrity across supply chains spanning OEMs, MRO organizations, airlines, lessors, and national regulators. Centralized data management systems — still dominant in the sector — expose the ecosystem to single points of failure and provide limited traceability of millions of aircraft parts circulating annually. This paper presents a structured review of blockchain-based security architectures for aviation networks, synthesized from 14 peer-reviewed sources published between 2018 and 2025, retrieved from IEEE Xplore, ScienceDirect, SpringerLink, ACM Digital Library, and Wiley/Hindawi. On this basis, a thirteen-step design method is proposed for integrating permissioned blockchain with distributed cloud infrastructure in aviation environments. The method is grounded in quantitative acceptance criteria — throughput ≥ 500 TPS, smart contract execution latency < 200 ms (p95), system availability 99.9% — and maps each design phase to specific security controls (integrity, access control, auditability, privacy, resilience, governance). Core mechanisms are formalized via hash-chain integrity verification, attribute-based access control functions, zero-knowledge proof verification, and a composite pre-ledger trust-scoring model. The principal finding: permissioned blockchain architectures — Hyperledger Fabric in particular — can support aviation requirements for immutable audit trails, decentralized identity management, and regulatory compliance with EASA and FAA; adoption remains constrained by organizational readiness and the unresolved GIGO problem at the ledger boundary.
Background: Airport security demands sub-second, high-throughput identity verification while increasingly stringent privacy regulation prohibits the centralized accumulation of passenger data. Existing deployments copy complete passenger profiles to every checkpoint terminal, multiplying the data breach surface at each journey touchpoint and conflicting with GDPR data minimization requirements. Methods: This paper presents BIPV (Blockchain-based Identity and Privacy Verification), a system that resolves this tension through programmable zero-knowledge proofs. BIPV anchors only cryptographic references on a Hyperledger Fabric consortium blockchain; passengers prove eligibility at checkpoints via Circom-compiled Groth16 zk-SNARKs that confirm policy compliance without disclosing any underlying personal attributes. We detail the Circom circuit design for airport policy predicates (AgeVerifier, NationalityChecker, DocumentValidator), a proof pre-computation and caching strategy that eliminates gate-lane latency, and a Hyperledger Fabric consortium governance model that anchors verification keys without recording passenger movement. Results: Our prototype achieves 0.42 s mean verification latency, 2,380 passengers per checkpoint per hour, and a 94.7% reduction in PII exposure relative to centralized baselines, evaluated across 1,000 simulated verification sessions. Security analysis confirms resistance to credential forgery, replay attacks, and consortium collusion under standard cryptographic assumptions. Conclusions: BIPV satisfies GDPR data minimization requirements, ICAO Annex 17, and IATA One ID guidelines. Beyond aviation, the BIPV model generalizes to any domain requiring high-assurance, high-throughput identity verification under privacy obligations.
The following paper presents research aimed at identifying the most critical risks and their mitigations in Urban Air Mobility (UAM) operations. This topic is one of aviation's most significant challenges in the coming decades. Having many flying vehicles in a single airspace requires an innovative approach, rule redefinition, and traffic management. Some solutions are scalable and can be adapted from general aviation. Therefore, stakeholders must address new risks and implement dedicated methods while maintaining the highest level of operational safety. Simulation research is needed to validate solutions before systems operate in real environments. The response to those challenges is the development of a simulation tool that can serve as a test benchmark. The study is divided into two sections: identifying potential risks associated with the rapidly growing UAV market and its applications in urban environments and developing a simulation tool that addresses various Urban Air Mobility challenges. A set of test cases is presented to demonstrate the tool’s functionality and capabilities for further analysis. The paper reviews the United States and European Union approaches to UAM integration, including NASA, FAA, SESAR, and EASA initiatives, and highlights differences in operational concepts and regulatory frameworks. The research identifies major categories of risks related to UAV operations, including technical failures, environmental hazards, human factors, and cybersecurity threats. Long-term challenges associated with increasing traffic density, autonomous operations, and airspace organization are also discussed. The research evaluates scalable safety solutions derived from commercial aviation and analyzes urban airspace concepts such as layers, zones, sky-lanes, and sky-corridors. The developed simulation environment, implemented for the Warsaw metropolitan area, enables modeling of large-scale UAV and VTOL operations, no-fly zones, vertiport hubs, and traffic distribution. The results demonstrate the importance of dedicated traffic structures, altitude separation, and decentralized traffic management systems in ensuring safe and efficient Urban Air Mobility operations.
Secure cross-domain UAV authentication is challenging because identity verification alone is insufficient to guarantee safe operation. In many UAV applications, it is equally critical to verify that a UAV is currently located within an authorized geographic region. Existing approaches often expose precise GPS coordinates, rely on static identifiers that enable tracking, or fail to guarantee the freshness and authenticity of location evidence. These weaknesses allow replay, location spoofing, and trajectory inference attacks, especially in multi-domain environments. To address these limitations, we propose PrivLocAuth, a zero-knowledge-based cross-domain UAV authentication protocol that enforces geofence restrictions without revealing actual locations. In PrivLocAuth, UAVs encode their current coordinates into fresh Pedersen commitments, which are attested by the home Local Domain Server (LDS) using short-lived Schnorr signatures. Based on these attested commitments, UAVs generate Bulletproof range proofs to demonstrate compliance with cross-domain server-defined geofences. This design ensures that UAVs operate within authorized airspace while preserving strong location privacy. PrivLocAuth further incorporates a lightweight elliptic curve cryptography (ECC) and Schnorr signature-based credential framework that enables unlinkable authentication across-domains, preventing session correlation and identity tracking. Formal security analysis demonstrates resistance to impersonation, replay, geofence-bypass, and linkage attacks. Experimental evaluation shows low computational latency and minimal communication overhead, confirming the protocol’s suitability for resource-constrained UAV platforms operating in dynamic cross-domain environments.
Distributed spectrum allocation for large-scale UAV swarm remains a challenging issue, due to spectrum allocation collisions and the high communication overhead required to reach consensus. To address these challenges, we propose a lightweight consensus protocol for distributed collision-free spectrum allocation (LCCFSA), where UAV nodes in the swarm form a blockchain and spectrum allocation consensus is reached on the chain. Specifically, a fast low-complexity allocation scheme is developed for each UAV based on an interference graph, where each UAV adaptively adjusts its occupancy area to avoid mutual interference. To further reduce the consensus overhead, we design a lightweight consensus protocol with a transaction-based blockchain ledger and provide a formal security analysis of the proposed protocol. A prototype is built to validate the feasibility of the proposed scheme. Simulation results show that the average consensus latency can be reduced by more than 20% in scenarios with 100 consensus nodes.
Low-altitude aerial networks play an increasingly critical role in urban logistics, emergency response, and intelligent airspace management. These networks must ensure reliable identity authentication while addressing privacy, efficiency, and security challenges. Traditional authentication mechanisms—such as PKI-based certificates and remote identification—either overexpose identity data or lack support for flexible attribute disclosure. Moreover, existing anonymous credential (AC) schemes, though offering privacy, often incur high computational and communication costs and exist vulnerable to replay attacks. To address these limitations, we proposeDVA-ACLF(Designated Verifier Asymmetric Anonymous Credential Scheme for Low-Altitude Flight), a lightweight credential system tailored for UAVs. DVA-ACLF leverages an efficient MAC-based construction combined with non-interactive zero-knowledge proofs to enable selective attribute disclosure without relying on pairings. It supports designated verification to prevent credential misuse and replay. Experimental results show that DVA-ACLF reduces credential size by 49% (2720 bits vs. 5369 bits in Idemix) and mitigates the linear growth of credential size with respect to attribute count observed in CL and BBS+ schemes. It requires only four single-base and$2(k-l)$double-base exponentiations on UAVs, where$k$is the number of selected attributes and$l$is the number of disclosed attributes—both typically small. These features make DVA-ACLF a strong candidate for secure, efficient, and privacy-preserving authentication in low-altitude flight applications.
The integration of decentralized security mechanisms into smart drone surveillance systems marks a transformative advancement in the field of unmanned aerial monitoring. Traditional centralized architectures are often vulnerable to single points of failure, data breaches and latency issues specifically in case of operation in hostile or remote environments. By leveraging blockchain technology, drone networks can establish a tamper-proof, distributed ledger that ensures the integrity and authenticity of surveillance data in real time. Internet of Drones is a decentralized network linking drones access to controlled airspace, providing high adaptability to complex scenarios and services to various drone applications such as package delivery, traffic surveillance and rescue including navigation services. One of the potential methods to enhance user privacy, data security and authentication, especially in peer-to-peer UAV networks is blockchain technology, which has now been gained prominence.
The integration of Uncrewed Aerial Vehicles (UAVs) into low-altitude airspace has led authorities to adopt distributed Uncrewed Traffic Management (UTM) architectures that ensure interoperability and safety. Blockchain has been proposed as an enabler for trustworthy coordination among UTM stakeholders. Yet, its real-time performance under aeronautical constraints remains insufficiently characterized. This paper presentes a quantitative benchmark comparing two regulation compliant distributed architectures: the federated InterUSS platform maintained by the Linux Foundation and a permissioned blockchain based on Hyperledger Fabric. Both systems were evaluated through Operational Intent Reference (OIR) registration work loads generated via Hyperledger Caliper, measuring throughput, latency, and transaction loss under loads up to 50 transactions per second. Results show that InterUSS sustained sub-second latency and stable performance up to 30 TPS. At the same time, Fabric exhibited exponential degradation with median latency exceeding 3 s and tail latencies above 15 s beyond that point. These findings demonstrate that blockchain-based architectures must be redesigned to meet aeronautical timing and scalability requirements, suggesting that hybrid models combining distributed ledgers for auditability with federated frameworks for real-time coordination are more suitable for future UTM deployments.
Unmanned Aerial Vehicles (UAVs) are increasingly deployed in inspection and monitoring missions, yet onboard computation and communication impose significant energy burdens that limit flight time and operational scope. In this work, we introduce a novel, blockchain-enabled framework-grounded in the Distributed Autonomous Organization (DAO) paradigm-for orchestrating distributed analytics across a swarm of UAVs. Leveraging the OASEES project's smart-contract architecture, each drone embeds a Metrics Module for real-time power monitoring, a Behavioral Module for adaptive control, and a Blockchain Agent that autonomously proposes, votes on, and executes collective decisions. Three concurrent threads-Proposal Trigger, Voting, and Action Execution-enable fully decentralized governance of swarm behavior: from detecting critical energy thresholds and formulating swarm-wide conservation maneuvers, to executing approved strategies across all members. We validate our framework in a UAV-based infrastructure inspection scenario, employing a YOLOv5 object-detection pipeline to classify four corrosion classes on a telecommunications mast under three video-capture modalities (short-distance, long-distance, and horizontally concatenated streams). Across all configurations, our system achieves near-perfect precision, recall, and mean Average Precision (mAP50-95$\approx 0.995$), demonstrating both the efficacy of distributed workload inference and the feasibility of treating a single drone as a multi-feed processor. These results underscore the potential of DAO-driven UAV swarms for energy-aware, resilient aerial analytics, and pave the way for fully decentralized 5G/6G-enabled airborne networks.
Hope Leticia Nakayiza, Love Allen Chijioke Ahakonye, Dong‐Seong Kim, Jae Min Lee
The growing deployment of unmanned aerial vehicles (UAVs) in military operations necessitates a secure, scalable, and decentralized approach to airspace management. This paper introduces MilChain-UAV, a blockchain-based traffic control framework tailored for military UAV networks. Built on PureChain, a custom permissioned blockchain network, MilChain-UAV supports autonomous mission governance, real-time path validation, and decentralized collision avoidance. To optimize blockchain efficiency while ensuring auditability, telemetry data is stored off-chain using IPFS, with only the cryptographic hashes anchored on-chain. By replacing centralized controllers with a distributed ledger, the framework enhances resilience against jamming and spoofing while enabling dynamic routing and verifiable behavior logging. Experimentation results demonstrate MilChain- UA V's effectiveness in improving efficiency and scalability in critical military operations, providing a robust solution for autonomous and secure management of military UAV traffic.
Lukas Sparer, Alexander Neulinger, Rigault Bastien, Artur Gonçalves · 7 authors
As the number of unmanned aerial vehicle (UAV) operations is growing rapidly, the risk of collisions increases significantly, making the coordination and verification of flight path compliance crucial. Since many different stakeholders, such as different UAV service suppliers (USS) and UAV operators are involved in an advanced air mobility (AAM) system, the system shall be decentralized and telemetry data shall be measured by the local community using sensor devices. In order to increase system resilience, sub-components of the system are implemented on a blockchain. Smart contracts are used to check whether a UAV has actually navigated the route specified by the USS pre-flight. Due to the restrictions of the system, the flight plan cannot be publicly revealed. Zero-Knowledge proofs (ZKPs) are unfeasible for this use case due to the high number of transactions and computational effort. Therefore, a novel approach has been developed that crosschecks measured telemetry data of UAV flights with flight plans and verifies the correctness without revealing any sensitive flight information. The verification results of UAV telemetry data can further be used to reward UAV operators for complying with the planned flight path.
the air traffic management (ATM) system is an important basic implementation to ensure the security of air transportation, and it is of great significance to research the security and privacy protection issues in ATM data sharing. At present, the data sharing among many ATM application systems is increasing, and there are considerable security risks in terms of security, integrity, privacy and efficiency. Blockchain is a representative distributed ledger technology, which has advantages in evidence traceability, multi-party collaboration, and information control that can be applied to the field of ATM data security sharing. This paper integrates blockchain-cloud storage application into ATM data sharing, and designs SATMChain, a blockchain-based ATM data sharing method. Focusing on the traceability and verification requirements in ATM data sharing, S-ATMChain realizes a new model of ATM data sharing that is trustworthy, secure, controllable, usable, and verifiable. Further, this paper designs smart contracts in three dimensions: ATM data identification, ATM data sharing control, and ATM data traceability-tracking to realize the security and privacy protection of the whole life cycle of ATM data. Finally, through the analysis and verification, the model and algorithm proposed in this paper have certain feasibility and advancement, achieve the expected effect, and have the prospect of practical application.
Digital passports for Unmanned Aerial Vehicles (UAVs) are used to create a unified system for tracking and identifying UAVs, which ensures compliance and security. A digital passport holds details like the owner's information, drone model, and activity history, thereby enabling easy tracking and identification of UAVs. However, the absence of decentralized and secure digital passport management systems for UAVs makes it challenging to ensure tamper-proof records and transparent ownership verification across borders. This paper proposes a proof of concept for a decentralized blockchain and Non-Fungible Tokens (NFTs)-based digital passport to improve the transparency, traceability, trust, and security of UAV preoperational certifications. The proposed solution secures UAVs' preoperational stages such as design, manufacturing, and distribution, integrating best practices from the Federal Aviation Administration (FAA) and the European Union Aviation Safety Agency (EASA) for standardized compliance. The proposed NFT-based digital passport consolidates certification records into a single verifiable document, providing access to compliance history. Four smart contracts are developed to enforce role-based access control, and off-chain decentralized storage using the InterPlanetary File System (IPFS) is employed to manage large UAV records. Evaluation through implementation and testing demonstrates the solution's effectiveness in managing UAV certification workflows and enforcing regulatory compliance. Security analysis shows robustness against unauthorized modifications and common vulnerabilities, while cost analysis assesses deployment viability across multiple blockchain networks. A comparison of the proposed solution with existing UAV compliance and certification frameworks shows that it effectively fills the gap by addressing preoperational certification. The smart contract code is publicly available on GitHub.
The increasing deployment of Unmanned Aerial Vehicles (UAVs) for military, commercial, and logistics applications has raised significant concerns regarding flight path privacy. Conventional UAV communication systems often expose flight path data to third parties, making them vulnerable to tracking, surveillance, and location inference attacks. Existing encryption techniques provide security but fail to ensure complete privacy, as adversaries can still infer movement patterns through metadata analysis. To address these challenges, we propose a zk-SNARK (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge)-based privacy preserving flight path authentication and verification framework. Our approach ensures that a UAV can prove its authorisation, validate its flight path with a control centre, and comply with regulatory constraints without revealing any sensitive trajectory information. By leveraging zk-SNARKs, the UAV can generate cryptographic proofs that verify compliance with predefined flight policies while keeping the exact path and location undisclosed. This method mitigates risks associated with real-time tracking, identity exposure, and unauthorised interception, thereby enhancing UAV operational security in adversarial environments. Our proposed solution balances privacy, security, and computational efficiency, making it suitable for resource-constrained UAVs in both civilian and military applications.
Environmental factors and electronic interference often disrupt communication between UAV swarms and ground control centers, requiring UAVs to complete missions autonomously in offline conditions. However, current coordination schemes for UAV swarms heavily depend on ground control, lacking robust mechanisms for offline task allocation and coordination, which compromises efficiency and security in disconnected settings. This limitation is especially critical for complex missions, such as rescue or attack operations, underscoring the need for a solution that ensures both mission continuity and communication security. To address these challenges, this paper proposes an offline task-coordination algorithm based on blockchain smart contracts. This algorithm integrates task allocation, resource scheduling, and coordination strategies directly into smart contracts, allowing UAV swarms to autonomously make decisions and coordinate tasks while offline. Experimental simulations confirm that the proposed algorithm effectively coordinates tasks and maintains communication security in offline states, significantly enhancing the swarm’s autonomous performance in complex, dynamic scenarios.
Non-Fungible Tokens (NFTs) have emerged as a revolutionary method for managing digital assets, providing transparency and secure ownership records on a blockchain. In this paper, we present a theoretical framework for leveraging NFTs to manage UAV (Unmanned Aerial Vehicle) flight data. Our approach focuses on ensuring data integrity, ownership transfer, and secure data sharing among stakeholders. This framework utilizes cryptographic methods, smart contracts, and access control mechanisms to enable a tamper-proof and privacy-preserving management system for UAV flight data.
Sana Hafeez, Runze Cheng, Lina Mohjazi, Yao Sun · 5 authors
Unmanned Aerial Vehicles (UAVs) have significant potential for agile communication and relief coordination in post-disaster scenarios, especially when conventional ground infrastructure is compromised. However, effectively coordinating and securing swarms of heterogeneous UAVs from multiple service providers presents critical challenges related to privacy, scalability, lightweight consensus protocols, and cybersecurity resilience. This study proposes a blockchain-enabled UAV coordination framework that leverages consensus mechanisms, smart contracts, and cryptographic techniques to address these challenges. First, a consortium blockchain architecture is introduced, integrating Zero-Knowledge Proofs (ZKPs) to enable privacy-preserving, multi-agency coordination while ensuring access control and data security. Second, a hybrid Delegated Proof-of-Stake–Practical Byzantine Fault Tolerance (DPoS-PBFT) consensus protocol is developed to optimise security, efficiency, and resilience against node failures in resource-constrained UAV networks. Third, a decentralized flocking algorithm is proposed to enable adaptive and autonomous UAV cluster operations under dynamically changing connectivity conditions, ensuring seamless disaster relief functions. Comprehensive simulations show that the proposed system scales efficiently to 500 UAV nodes while maintaining high throughput and low latency, with only a 50-ms increase in latency from 10 to 500 nodes. The framework demonstrates strong cyber resilience, remaining robust under denial-of-service (DoS), spoofing, and tampering attacks. Furthermore, communication latencies remain under 10 milliseconds, with median values of approximately 2–3 ms, achieved through self-optimizing network intelligence. The results validate the proposed system as a secure, scalable, and high-performance solution for UAV-enabled disaster response, ensuring reliable emergency communication and efficient resource allocation in critical environments.
Abstract One of the main objectives of the European Commission (EC) since the 70s has been to coordinate research policies and to enhance the transnational cooperation in order to reach efficiency in terms of funding and to match with Europe’s economic ambitions. It has been addressed through a centralized approach managed by the EC and a decentralized approach through the cooperation of member states. Regarding the aviation sector, the centralized financing has been successfully implemented under the EU Research & Innovation Framework Programmes, while the decentralized approach has been less successful through the initiative Air Transport Net (AirTN) ERA-NET. The intention of this paper is to analyse the AirTN case study and its methodology to launch transnational calls, the results, and the reasons why it was not completely successful. Following the identification of these main barriers, we provide a list of suggestions that could have been implemented for a more successful outcome.
the air traffic management (ATM) system is a comprehensive information-based intelligent system that provides seamless services and dynamic integrated management of air traffic and airspace through the cooperation of all relevant parties in civil aviation. The ATM adopts an integrated “space-air-ground” network structure to provide reliable services for the security and efficiency of civil aviation flights, which is an important infrastructure to support and guarantee civil aviation transportation and an important support point for the development of civil aviation as a whole. The composition of the ATM is wide and complex, and contains many business systems and user types. In the face of the increasingly serious information security threats, the business collaboration of ATM and the shared use of ATM data are subject to certain restrictions and challenges. According to the Aviation Network Security Strategy released by International Civil Aviation Organization (ICAO) in 2019, there is an urgent need to research the basic theories, core methods and key technologies for ATM information security assurance that are compatible with the characteristics of ATM composition and information security assurance needs. From the core research objective of ATM information security assurance, this paper designs a future ATM security architecture based on blockchain technology, referred to as ATMChain, to meet the real operational needs of ATM trustworthiness, security and availability. ATMChain takes ATM trustworthy services as the core and builds an ATM information security base with “endogenous security” features. Then, three security function modules, namely, trusted authentication, data sharing, and access control, are designed to realize the 4A (Authentication, Account, Audit, Authorization) security functions of ATM. Finally, this paper provides a comprehensive analysis and performance evaluation of ATMChain security architecture. The results show that the research in this paper will help solve the current bottlenecks in ATM information security assurance, promote technological innovation, and ultimately facilitate the realization of the vision of global ATM interoperability proposed by ICAO.
Seyed Mohammad Hashemi, Ruxandra Mihaela Botez, Georges Ghazi
This paper introduces an innovative consensus algorithm for managing Unmanned Aircraft System Traffic (UTM) through blockchain technology, a highly secure consensus protocol, to allocate airspace. A smart contract was developed on the Ethereum blockchain for allocating airspace. This technique enables the division of the swarm flight zone into smaller sectors to decrease the computational complexity of the algorithm. A decentralized voting system was established within these segmented flight zones, utilizing two primary methodologies: Proof of Work (PoW) and Proof of Stake (PoS). By employing 1000 UAS-S4s across various locations and heading angles, a swarm flight zone was generated. The efficiency of the devised decentralized consensus system was assessed based on error rate and validation time. Despite PoS displaying greater efficiency in cumulative probability for block execution, the comparative analysis indicated PoW outperformed PoS concerning the potential for conflicts among UASs.