# A Multi-Layer Secure Sharing Framework for Aviation Big Data Based on Blockchain
###### Abstract  
As a new type of production factor, data possesses multidimensional application value, and its pivotal role is becoming increasingly prominent in the aviation sector. Data sharing can significantly enhance the utilization efficiency of data resources and serves as one of the key tasks in building smart civil aviation. However, currently, data silos are pervasive, with vast amounts of data only being utilized and analyzed within limited scopes, leaving their full potential untapped. The challenges in data sharing primarily stem from three aspects: (1) Data owners harbor concerns regarding data security and privacy. (2) The highly dynamic and real-time nature of aviation operations imposes stringent requirements on the timeliness, stability, and reliability of data sharing, thereby constraining its scope and extent. (3) The lack of reasonable incentive mechanisms results in insufficient motivation for data owners to share. Consequently, addressing the issue of aviation big data sharing holds significant importance. Since the release of the Bitcoin whitepaper in 2008, blockchain technology has achieved continuous breakthroughs in the fields of data security and collaborative computing. Its unique characteristics--decentralization, tamper-proofing, traceability, and scalability--lay the foundation for its integration with aviation. Blockchain can deeply integrate with air traffic management (ATM) operations, effectively resolving trust, efficiency, and collaboration challenges in distributed scenarios for ATM data. To address the heterogeneous data usage requirements of different ATM stakeholders, this paper constructs a blockchain-based multi-level data security sharing architecture, enabling fine-grained management and secure collaboration. Furthermore, to meet the stringent timeliness demands of aviation operations and the storage pressure posed by massive data, this paper optimizes blockchain storage deployment and consensus mechanisms, thereby enhancing system scalability and processing efficiency. Additionally, a dual-mode data-sharing solution combining raw data sharing and model sharing is proposed, offering a novel approach to aviation big data sharing. Security and formal analyses demonstrate that the proposed solution is both secure and effective. a [figure]style=plain,color=gray!20,color=gray!20,color=gray! strong developmental momentum. Data, as a key element of production, is increasingly demonstrating its multidimensional value in aviation. From an operational perspective, air traffic management (ATM) data reflects the real-time status of aviation activities, providing precise situational awareness and decision-making support for stakeholders (e.g., air traffic controllers, airlines, airports), such as real-time weather information sharing, flight conflict warnings, and dynamic traffic management. From a research perspective, ATM data serves as an empirical foundation for exploring aviation operational patterns, validating optimization strategies, and developing intelligent decision-making systems. Data-driven aviation has become a consensus, and data sharing can significantly enhance data resource utilization, serving as a critical task in building smart civil aviation. However, data silos persist, with vast amounts of data only accessible and analyzable within limited scopes, leaving their potential underutilized. The challenges in data sharing stem from three main factors: (1) Security and privacy concerns: Aviation data, especially ATM data, contains sensitive operational information with high security requirements. Recent privacy breaches in aviation, such as the 21 May 2021, incident where Indian Airlines reported the theft of approximately 4.5 million customer records spanning a decade (August 2011 to February 2021), have heightened data owners' apprehensions. (2) Dynamic and real-time requirements: The highly dynamic nature of aviation operations imposes stringent demands on the timeliness, security, and reliability of data sharing, limiting its scope and extent.