A Cryptoeconomic Traffic Analysis of Bitcoin's Lightning Network
This work addresses scalability and privacy issues for Bitcoin users, but it is incremental as it builds on existing analysis with new simulations.
The authors tackled the economic viability and privacy of Bitcoin's Lightning Network by simulating traffic, finding that most large routing nodes operate at a loss and that privacy is weak due to short paths, with a proposed method to improve privacy at low cost.
Lightning Network (LN) is designed to amend the scalability and privacy issues of Bitcoin. It's a payment channel network where Bitcoin transactions are issued off chain, onion routed through a private payment path with the aim to settle transactions in a faster, cheaper, and private manner, as they're not recorded in a costly-to-maintain, slow, and public ledger. In this work, we design a traffic simulator to empirically study LN's transaction fees and privacy provisions. The simulator relies on publicly available data of the network structure and generates transactions under assumptions we attempt to validate based on information spread by certain blog posts of LN node owners. Our findings on the estimated revenue from transaction fees are in line with widespread opinion that participation is economically irrational for the majority of large routing nodes who currently hold the network together. Either traffic or transaction fees must increase by orders of magnitude to make payment routing economically viable. We give worst-case estimates for the potential fee increase by assuming strong price competition among the routers. We estimate how current channel structures and pricing policies respond to a potential increase in traffic, how reduction in locked funds on channels would affect the network, and show examples of nodes who are estimated to operate with economically feasible revenue. Even if transactions are onion routed, strong statistical evidence on payment source and destination can be inferred, as many transaction paths only consist of a single intermediary by the side effect of LN's small-world nature. Based on our simulation experiments, we quantitatively characterize the privacy shortcomings of current LN operation, and propose a method to inject additional hops in routing paths to demonstrate how privacy can be strengthened with very little additional transactional cost.