Implementing Blockchain in the Airline Sector

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Implementing Blockchain in the Airline Sector

Abuayied, Samah / Alajlan, Fatimah / Alghamdi, Alshymaa

Blockchain is a distributed database with specific properties and elements in the idea of Bitcoin, which is a combination of peer to peer networks, software, and protocols. Currently, many companies start to adopt blockchain in their systems to enhance the rate of security and data integrity. However, blockchain has proved its ability in different life fields, such as education, healthcare, government, and industry. However, as a result of the increasing rate of airline transportation issues, there was a high demand to activate blockchain in aviation to prove robustness solutions. However, airline transportation had been evolving by decades, and to preserve these rates of evolution, it needs to integrate new technologies in the airline sector. The main features of the blockchain that make it useful in improving air transportation routes are its ability to store any information such as events, object transactions, and electronic transactions. Moreover, the blockchain can provide legal support for flights and managing passenger information and airline flights to solve issues related to transparency, and control. In this paper we give the first steps to a scientific comprehensive literature review that present a detailed of the current investigations and studies in introducing blockchain in the airline sector. Besides, the paper introduce the main challenges, assumptions, advantages, and future work in integrating blockchain in airline sector as a way for enhancing public transportation and human life.

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Dokumentinformationen

Titel :

Implementing Blockchain in the Airline Sector

Weitere Titelangaben:

Algorithms for Intelligent Systems

Beteiligte:

Hassanien, Aboul Ella (Herausgeber:in) / Darwish, Ashraf (Herausgeber:in) / Abd El-Kader, Sherine M. (Herausgeber:in) / Alboaneen, Dabiah Ahmed (Herausgeber:in) / Abuayied, Samah (Autor:in) / Alajlan, Fatimah (Autor:in) / Alghamdi, Alshymaa (Autor:in)

Erschienen in:

Enabling Machine Learning Applications in Data Science ; Kapitel : 27 ; 379-388

Algorithms for Intelligent Systems

Erscheinungsdatum :

2021-05-28

Format / Umfang :

10 pages

ISBN :

978-981-33-6129-4 , 978-981-33-6128-7

ISSN :

2524-7573 , 2524-7565

DOI :