Improving the Anonymity of Blockchains: The Case of Payment Channel Networks with Length-bounded Random Walk Insertion

Bachelor thesis (2021)

Authors

M.E. Özkan Electrical Engineering, Mathematics and Computer Science

Contributors

S. Roos Data-Intensive Systems - EEMCS (mentor)
S. Prabhu Kumble Data-Intensive Systems - EEMCS (mentor)
D. Spinellis Software Engineering - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2021 Emre Özkan
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Published Date

01-07-2021

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

The LND is currently the most popular routing algorithm used in the Lightning Network, the second layer solution to Bitcoin’s scalability. Despite its popularity, recent studies demonstrate that its deterministic nature compromises the anonymity of the Lightning Network. In other words, threatening parties present in the transaction path can guess the sending and receiving parties of transactions easier than in the absence of such strong determinism. As a solution, we propose augmenting the LND with a length bounded random walk insertion to include randomness into the transaction path and regain anonymity. Most importantly, we found that for generated network simulations and the snapshot network, including the random walk into the transaction path improves anonymity. In simulations with LND routing, attackers could identify senders or
receivers for 70% of transactions. For simulations of networks with 100 nodes and an average of 2 edges per node with the weighted random walk insertion, attackers could identify senders or receivers around 65% of the time. However, for simulations of networks with 500 nodes and an average of 10 edges per node with the weighted random walk insertion, attackers could never identify senders or receivers. Besides, for the snapshot simulation, they could only identify either in around 4% of transactions. Thus, we overall believe that the random walk insertion into the LND algorithm addresses the anonymity issue of the unmodified algorithm.