Optimizing Virtual Payment Channel Establishment in the Face of On-Path Adversaries

Payment channel networks (PCNs) are among the most promising solutions to the scalability issues in permissionless blockchains, by allowing parties to pay each other off-chain through a path of payment channels (PCs). However, routing transactions comes at a cost which is proportional to the number of intermediaries, since each charges a fee for the routing service. Furthermore, analogous to other networks, malicious intermediaries in the payment path can lead to security and privacy threats. Virtual channels (VCs), i.e., bridges over PC paths, mitigate the above PCN issues, as after the VC creation, intermediaries are excluded from every VC transaction. However, creating a VC has a cost that must be paid out of the bridged PCs' balance. Currently, we are missing guidelines on how and where to best set up VCs. In this work, we address this VC-setup problem, formalizing it as an optimization problem. We present an integer linear program (ILP) to compute the globally optimal VC-setup strategy in terms of fees, security, and privacy. We then accompany the computationally heavy ILP with a fast local greedy algorithm. Our solutions can be used with any on-path adversary, given that its strategy can be expressed as a set of corrupted nodes that is estimated by the honest nodes. We evaluate our greedy algorithm over a Lightning Network (LN) snapshot, the largest PCN. Our findings confirm that our greedy strategy minimizes costs while protecting against threats of on-path adversaries and may serve the LN community as guidelines for the deployment of VCs.