Zhonghui Ge (Shanghai Jiao Tong University), Yi Zhang (Shanghai Jiao Tong University), Yu Long (Shanghai Jiao Tong University), Dawu Gu (Shanghai Jiao Tong University)

A leading approach to enhancing the performance and scalability of permissionless blockchains is to use the payment channel, which allows two users to perform off-chain payments with almost unlimited frequency. By linking payment channels together to form a payment channel network, users connected by a path of channels can perform off-chain payments rapidly. However, payment channels risk encountering fund depletion, which threatens the availability of both the payment channel and network. The most recent method needs a cycle-based channel rebalancing procedure, which requires a fair leader and users with rebalancing demands forming directed cycles in the network. Therefore, its large-scale applications are restricted.

In this work, we introduce Shaduf, a novel non-cycle off-chain rebalancing protocol that offers a new solution for users to shift coins between channels directly without relying on the cycle setting. Shaduf can be applied to more general rebalancing scenarios. We provide the details of Shaduf and formally prove its security under the Universal Composability framework. Our prototype demonstrates its feasibility and the experimental evaluation shows that Shaduf enhances the Lighting Network performance in payment success ratio and volume. Moreover, our protocol prominently reduces users’ deposits in channels while maintaining the same amount of payments.

View More Papers

Privacy in Urban Sensing with Instrumented Fleets, Using Air...

Ismi Abidi (IIT Delhi), Ishan Nangia (MPI-SWS), Paarijaat Aditya (Nokia Bell Labs), Rijurekha Sen (IIT Delhi)

Read More

Building Embedded Systems Like It’s 1996

Ruotong Yu (Stevens Institute of Technology, University of Utah), Francesca Del Nin (University of Padua), Yuchen Zhang (Stevens Institute of Technology), Shan Huang (Stevens Institute of Technology), Pallavi Kaliyar (Norwegian University of Science and Technology), Sarah Zakto (Cyber Independent Testing Lab), Mauro Conti (University of Padua, Delft University of Technology), Georgios Portokalidis (Stevens Institute of…

Read More

DRIVETRUTH: Automated Autonomous Driving Dataset Generation for Security Applications

Raymond Muller (Purdue University), Yanmao Man (University of Arizona), Z. Berkay Celik (Purdue University), Ming Li (University of Arizona) and Ryan Gerdes (Virginia Tech)

Read More

ATTEQ-NN: Attention-based QoE-aware Evasive Backdoor Attacks

Xueluan Gong (Wuhan University), Yanjiao Chen (Zhejiang University), Jianshuo Dong (Wuhan University), Qian Wang (Wuhan University)

Read More