Payment channel networks (PCNs) provide a faster and cheaper alternative to transactions recorded on the blockchain. Clients can trustlessly establish payment channels with relays by locking coins and then send signed payments that shift coin balances over the network's channels. Although payments are never published, anyone can track a client's payment by monitoring changes in coin balances over the network's channels [23, 31]. We present Twilight, the first PCN that provides a rigorous differential privacy guarantee to its users. Relays in Twilight run a noisy payment processing mechanism that hides the payments they carry. This mechanism increases the relay's cost, so Twilight combats selfish relays that wish to avoid it using a trusted execution environment (TEE) that ensures they follow its protocol. The TEE does not store the channel's state, which minimizes the trusted computing base. Crucially, Twilight ensures that even if a relay breaks the TEE's security, it cannot break the integrity of the PCN. We analyze Twilight in terms of privacy and cost and study the trade-off between them. We implement Twilight using Intel's SGX framework and evaluate its performance using relays deployed on two continents. We show that a route consisting of 4 relays handles 820 payments/sec.
|Original language||American English|
|Title of host publication||Proceedings of the 31st USENIX Security Symposium, Security 2022|
|Number of pages||16|
|State||Published - 2022|
|Event||31st USENIX Security Symposium, Security 2022 - Boston, United States|
Duration: 10 Aug 2022 → 12 Aug 2022
|Name||Proceedings of the 31st USENIX Security Symposium, Security 2022|
|Conference||31st USENIX Security Symposium, Security 2022|
|Period||10/08/22 → 12/08/22|
Bibliographical noteFunding Information:
We thank Adam D. Smith and Katrina Ligett for insightful discussions on differential privacy and its applications, and our shepherd Stefanie Roos. Yossi Gilad was partially supported by the Alon fellowship and the Hebrew University cyber security research center and a gift from Microsoft. Aviv Zohar, Maya Dotan, and Saar Tochner were partially supported by grants from the Israel Science Foundation (grants 1504/17 & 1443/21) and by a grant from the Hebrew University cyber security research center.
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