基于云-区块链-融合的空中交通管理安全共享模型

IF 1.3 4区 工程技术 Q2 ENGINEERING, AEROSPACE
Qing Wang, Lizhe Zhang, Xin Lu
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引用次数: 0

摘要

数据共享是维持空中交通管理(ATM)持续运行的基石。随着态势感知和协同决策成为智能 ATM 的重要组成部分,数据共享能力成为制约 ATM 发展的因素。现有的 ATM 数据共享解决方案存在以下问题:1) 数据共享效率低;2) 数据安全未得到足够重视;3) 访问控制难以实现。因此,提出了一种基于云-区块链融合的ATM安全数据共享模型,实现了数据安全存储、智能服务治理和数据授权访问。首先,定义了一套元文件存储结构,实现数据和元数据的分离存储,提供完整性验证和加密存储。此外,利用基于属性的加密和服务检索算法,实现了基于智能合约的数据发布、发现和调用功能。最后,该方案实现了 ATM 环境下的安全数据共享,与其他现有方案相比,计算成本和时间成本也保持在可接受的水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloud-Blockchain-Fusion–Based Secure Sharing Model for Air Traffic Management

Data sharing is the keystone to maintain the continuous operation of air traffic management (ATM). As situational awareness and collaborative decision-making become significant components of smart ATM, data sharing capability becomes a constraint on the development of ATM. The existing ATM data-sharing solutions have the following issues: 1) data-sharing efficiency is low; 2) data security has not received sufficient attention; and 3) access control is difficult to implement. Therefore, a security data-sharing model for ATM based on cloud-blockchain fusion is proposed, which realizes data security storage, intelligent service governance, and data authorized access. Firstly, a set of metafile storage structures is defined to realize the separate storage of data and metadata, which provides integrity verification and encrypted storage. Besides, using attribute-based encryption and service retrieval algorithms, the data publishing, discovery, and invocation functions based on smart contracts are realized. Finally, this scheme realizes secure data sharing in the ATM environment, and the computational cost and time cost are also kept at an acceptable level compared with other existing schemes.

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来源期刊
CiteScore
3.70
自引率
13.30%
发文量
58
审稿时长
>12 weeks
期刊介绍: This Journal is devoted to the dissemination of original archival research papers describing new theoretical developments, novel applications, and case studies regarding advances in aerospace computing, information, and networks and communication systems that address aerospace-specific issues. Issues related to signal processing, electromagnetics, antenna theory, and the basic networking hardware transmission technologies of a network are not within the scope of this journal. Topics include aerospace systems and software engineering; verification and validation of embedded systems; the field known as ‘big data,’ data analytics, machine learning, and knowledge management for aerospace systems; human-automation interaction and systems health management for aerospace systems. Applications of autonomous systems, systems engineering principles, and safety and mission assurance are of particular interest. The Journal also features Technical Notes that discuss particular technical innovations or applications in the topics described above. Papers are also sought that rigorously review the results of recent research developments. In addition to original research papers and reviews, the journal publishes articles that review books, conferences, social media, and new educational modes applicable to the scope of the Journal.
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