Proof of Liabilities
Companies that accept monetary deposits from consumers, such as banks, blockchain custodial wallets and gambling companies, are periodically being audited for accounting and oftentimes financial solvency purposes. Traditionally, a third party auditor undertakes the role of verifying solvency by cross-checking transaction records in the company books. However, decentralized solutions that require customers to jointly participate in the auditing process have been recently proposed as an alternative or complementary method to conventional audit processes. Cryptographic proof of liabilities (PoL) is a cryptographic primitive to prove the size of funds a bank owes to its customers in a decentralized manner and can be used for solvency audits with better privacy guarantees. Most PoL schemes follow the same principle, i.e., a prover aggregates all of the user balances and enables users to verify balance inclusion in the reported total amount. This process is probabilistic and the more the users who verify inclusion the better the guarantee of a non-cheating prover. In this presentation, Yan Ji introduces generalized PoL, which was originally proposed for proving financial solvency, by extending the state-of-the-art PoL scheme with extra privacy features, and making it applicable to domains outside finance, including transparent and private donations, new algorithms for disapproval voting and negative reviews, and publicly verifiable COVID-19 cases.
Yan Ji is pursuing her PhD in Computer Science at Cornell University under the supervision of Prof. Ari Juels. Her research interest focuses on blockchain scalability, research ethics and legal compliance. In particular, her research aims to design efficient and secure blockchain protocols, and concurrently introduce and examine principles for conducting ethical blockchain research. In the future, she plans to provide guidelines for ethical blockchain research and design new frameworks of legal compliance and infringement prevention for blockchain applications.