论文标题
计算雷声：付款渠道网络中隐私的时机攻击
Counting Down Thunder: Timing Attacks on Privacy in Payment Channel Networks
论文作者
论文摘要
闪电网络是比特币的扩展解决方案，有望实现快速和私人的支付处理。在闪电中，多跳付款是通过利用哈希的时间锁定合同（HTLC）来确保的，并通过洋葱路由方案在网络层上加密，以避免信息泄漏到中间节点。然而，在这项工作中，我们表明，闪电网络的隐私保证可能会被对htlc状态谈判消息的定时攻击的按照对手颠覆。为此，我们提供了使对手可以减少匿名集并推断最有可能的付款终点的估计器。我们开发了概念验证测量节点，该节点显示了达到时间差异并评估基于模型网络模拟的对抗性成功的可行性。我们发现，控制一个少数恶意节点足以观察所有付款中的很大一部分，从而强调了On Path对手模型的相关性。此外，我们表明，不同幅度的对手可以采用基于计时的攻击，以高精度和召回方式将付款端点脱颖而出。
The Lightning Network is a scaling solution for Bitcoin that promises to enable rapid and private payment processing. In Lightning, multi-hop payments are secured by utilizing Hashed Time-Locked Contracts (HTLCs) and encrypted on the network layer by an onion routing scheme to avoid information leakage to intermediate nodes. In this work, we however show that the privacy guarantees of the Lightning Network may be subverted by an on-path adversary conducting timing attacks on the HTLC state negotiation messages. To this end, we provide estimators that enable an adversary to reduce the anonymity set and infer the likeliest payment endpoints. We developed a proof-of-concept measurement node that shows the feasibility of attaining time differences and evaluate the adversarial success in model-based network simulations. We find that controlling a small number malicious nodes is sufficient to observe a large share of all payments, emphasizing the relevance of the on-path adversary model. Moreover, we show that adversaries of different magnitudes could employ timing-based attacks to deanonymize payment endpoints with high precision and recall.
