  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.
