Giulia Scaffino (TU Wien), Lukas Aumayr (TU Wien), Mahsa Bastankhah (Princeton University), Zeta Avarikioti (TU Wien), Matteo Maffei (TU Wien)

Over the past decade, cryptocurrencies have garnered attention from academia and industry alike, fostering a diverse blockchain ecosystem and novel applications. The inception of bridges improved interoperability, enabling asset transfers across different blockchains to capitalize on their unique features. Despite their surge in popularity and the emergence of Decentralized Finance (DeFi), trustless bridge protocols remain inefficient, either relaying too much information (e.g., light-client-based bridges) or demanding expensive computation (e.g., zk-based bridges). These inefficiencies arise because existing bridges securely prove a transaction's on-chain inclusion on another blockchain. Yet this is unnecessary as off-chain solutions, like payment and state channels, permit safe transactions without on-chain publication. However, existing bridges do not support the verification of off-chain payments.

This paper fills this gap by introducing the concept of Pay2Chain bridges that leverage the advantages of off-chain solutions like payment channels to overcome current bridges' limitations. Our proposed Pay2Chain bridge, named Alba, facilitates the efficient, secure, and trustless execution of conditional payments or smart contracts on a target blockchain based on off-chain events. Alba, besides its technical advantages, enriches the source blockchain's ecosystem by facilitating DeFi applications, multi-asset payment channels, and optimistic stateful off-chain computation.

We formalize the security of Alba against Byzantine adversaries in the UC framework and complement it with a game theoretic analysis. We further introduce formal scalability metrics to demonstrate Alba's efficiency. Our empirical evaluation confirms Alba's efficiency in terms of communication complexity and on-chain costs, with its optimistic case incurring only twice the cost of a standard Ethereum transaction of token ownership transfer.

View More Papers

The Discriminative Power of Cross-layer RTTs in Fingerprinting Proxy...

Diwen Xue (University of Michigan), Robert Stanley (University of Michigan), Piyush Kumar (University of Michigan), Roya Ensafi (University of Michigan)

Read More

Secure Transformer Inference Made Non-interactive

Jiawen Zhang (Zhejiang University), Xinpeng Yang (Zhejiang University), Lipeng He (University of Waterloo), Kejia Chen (Zhejiang University), Wen-jie Lu (Zhejiang University), Yinghao Wang (Zhejiang University), Xiaoyang Hou (Zhejiang University), Jian Liu (Zhejiang University), Kui Ren (Zhejiang University), Xiaohu Yang (Zhejiang University)

Read More

Truman: Constructing Device Behavior Models from OS Drivers to...

Zheyu Ma (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University; EPFL; JCSS, Tsinghua University (INSC) - Science City (Guangzhou) Digital Technology Group Co., Ltd.), Qiang Liu (EPFL), Zheming Li (Institute for Network Sciences and Cyberspace (INSC), Tsinghua University; JCSS, Tsinghua University (INSC) - Science City (Guangzhou) Digital Technology Group Co., Ltd.), Tingting Yin (Zhongguancun…

Read More