Avarikioti, G., Bastankhah, M., Maddah-Ali, M. A., Pietrzak, K., Svoboda, J., & Yeo, M. (2024). Route Discovery in Private Payment Channel Networks. In DPM & CBT 2024 Pre-proceedings (pp. 195–211). http://hdl.handle.net/20.500.12708/210627
In this work, we explore route discovery in private payment channel networks. We first determine what “ideal” privacy for a routing protocol means in this setting. We observe that protocols achieving this strong privacy definition exist by leveraging Multi-Party Computation but they are inherently inefficient as they must involve the entire network. We then present protocols with weaker privacy guarantees but much better efficiency (involving only a small fraction of the nodes). The core idea is that both sender and receiver gossip a message which propagates through the network, and the moment any node in the network receives both messages, a path is found. In our first protocol the message is always sent to all neighbouring nodes with a delay proportional to the fees of that edge. In our second protocol the message is only sent to one
neighbour chosen randomly with a probability proportional to its degree.We additionally propose a more realistic notion of privacy in order to measure the privacy leakage of our protocols in practice. Our realistic notion of privacy challenges an adversary that join the network with a
fixed budget to create channels to guess the sender and receiver of a transaction upon receiving messages from our protocols. Simulations of our protocols on the Lightning network topology (for random transactions and uniform fees) show that 1) forming edges with high degree nodes is a more effective attack strategy for the adversary, 2) there is a tradeoff between the number of nodes involved in our protocols (privacy) and the optimality of the discovered path, and 3) our protocols involve a very small fraction of the network on average.
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Project (external):
ERC CoG ForM-SMArt Austrian Science Fund (FWF) Data-Driven Distributed Algorithms