The Lightning Network (LN) is a prominent payment channel network aimed at addressing Bitcoin's scalability issues. Due to the privacy of channel balances, senders cannot reliably choose sufficiently liquid payment paths and resort to a trial-and-error approach, trying multiple paths until one succeeds. This leaks private information and decreases payment reliability, which harms the user experience. This work focuses on the reliability and privacy of LN payments. We create a probabilistic model of the payment process in the LN, accounting for the uncertainty of the channel balances. This enables us to express payment success probabilities for a given payment amount and a path. Applying negative Bernoulli trials for single- and multi-part payments allows us to compute the expected number of payment attempts for a given amount, sender, and receiver. As a consequence, we analytically derive the optimal number of parts into which one should split a payment to minimize the expected number of attempts. This methodology allows us to define service level objectives and quantify how much private information leaks to the sender as a side effect of payment attempts. We propose an optimized path selection algorithm that does not require a protocol upgrade. Namely, we suggest that nodes prioritize paths that are most likely to succeed while making payment attempts. A simulation based on the real-world LN topology shows that this method reduces the average number of payment attempts by 20% compared to a baseline algorithm similar to the ones used in practice. This improvement will increase to 48% if the LN protocol is upgraded to implement the channel rebalancing proposal described in BOLT14.
翻译:闪亮网络( LN) 是一个重要的支付渠道网络, 目的是解决比特币的可缩放性问题。 由于频道平衡的隐私性, 发送者无法可靠地选择足够液态的支付路径, 并采用试错方法, 尝试多条路径直到一个成功。 这泄漏了私人信息, 降低了支付可靠性, 从而伤害了用户的经验。 这项工作侧重于LN付款的可靠性和隐私。 我们为LN支付过程创建了一个概率模型, 计算频道余额的不确定性。 这使我们能够表示给定的支付金额和路径的付款成功概率。 对单项和多部分付款适用负面的Bernoulli 测试, 并让我们计算给给给给定的数额、 发送者和接收者的预期付款尝试次数。 因此, 我们从分析地推算出一个最佳部分, 将付款分成一个部分, 以尽量减少预期的尝试次数。 这个方法让我们确定服务级别目标, 并量化有多少私人信息泄漏给发送者, 作为支付尝试的侧效果。 我们提议一个最优化路径选择单程, 将比比的路径选择方法更高级的路径, 将比重的路径比重更高级的路径, 将使用LLRLLRT。