Topological Analysis of Bitcoin’s Lightning Network

István András Seres (), László Gulyás (), Dániel A. Nagy () and Péter Burcsi ()
Additional contact information
István András Seres: Eötvös Loránd University
László Gulyás: Eötvös Loránd University
Dániel A. Nagy: Eötvös Loránd University
Péter Burcsi: Eötvös Loránd University

A chapter in Mathematical Research for Blockchain Economy, 2020, pp 1-12 from Springer

Abstract: Abstract Bitcoin’s Lightning Network (LN) is a scalability solution for Bitcoin allowing transactions to be issued with negligible fees and settled instantly at scale. In order to use LN, funds need to be locked in payment channels on the Bitcoin blockchain (Layer-1) for subsequent use in LN (Layer-2). LN is comprised of many payment channels forming a payment channel network. LN’s promise is that relatively few payment channels already enable anyone to efficiently, securely and privately route payments across the whole network. In this paper, we quantify the structural properties of LN and argue that LN’s current topological properties can be ameliorated in order to improve the security of LN, enabling it to reach its true potential.

Keywords: Bitcoin; Lightning network; Network security; Network topology; Payment channel network; Network robustness (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (2)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-37110-4_1

Ordering information: This item can be ordered from
http://www.springer.com/9783030371104

DOI: 10.1007/978-3-030-37110-4_1

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().