Distributed Auditing Proofs of Liabilities

Abstract

Distributed Auditing Proofs of Liabilities (DAPOL) provides a novel zero knowledge proof solution to a particular class of auditing cases, in which we assume that the audited entity does not have any incentive to increase its liabilities or obligations. There are numerous domains requiring such an auditing feature, including proving financial solvency, transparent fundraising campaigns and accurate lottery jackpot amounts. Additionally, the algorithm provides a solution to official reports, such as in COVID-19 published daily cases, unemployment rate announcements and decentralized product/service rating reviews. Interestingly, it can also be used as a cryptographic primitive for novel e-voting systems (i.e., disapproval voting and counting dislikes), and for innovative private syndicated loan/insurance solutions, new methods for decentralized credit scoring and user ranking, among the others. Compared to conventional auditor-based approaches, DAPOL provides a privacy preserving mechanism for users to validate their vote or amount inclusion in the reported total of liabilities/obligations and complements the traditional validation performed by the auditors by adding extra privacy and fairness guarantees. The recommended approach combines previously known cryptographic techniques to provide a layered solution with predefined levels of privacy in the form of gadgets. The backbone of this proposal is based on the enhanced Maxwell Merkle-tree construction and is extended using zero knowledge proofs, sparse trees, balance splitting tricks, efficient padding, verifiable random functions, deterministic key derivation functions and the range proof techniques from Provisions and ZeroLedge solvency protocols, respectively