Tax Declaration Scheme Using Blockchain Confidential Transactions

Author:

Sakalauskas Eligijus,Bendoraitis Antanas,Lukšaitė Dalė,Butkus Gintaras,Vitkutė-Adžgauskienė Daiva

Abstract

The article presents the tax declaration scheme using blockchain confidential transactions based on the modified ElGamal encryption providing additively-homomorphic property. Transactions are based on the unspent transactions output (UTxO) paradigm allowing to effectively represent digital asset of cryptocurrencies in e-wallets and to perform financial operations. The main actors around transaction are specified, include money senders, receivers, transaction creator, Audit Authority (AA) and Net of users. A general transaction model with M inputs and N outputs is created, providing transaction amount confidentiality and verifiability for all actors with different levels of available information. The transaction model allows Net to verify the validity of a transaction, having access only to encrypted transaction data. Each money receiver is able to decrypt and verify the actual sum that is transferred by the sender. AA is provided with actual transaction values and is able to supervise the tax payments for business actors. Such information allows to verify the honesty of transaction data for each user role. The security analysis of the scheme is presented, referencing to ElGamal security assumptions. The coalition attack is formulated and prevention of this attack is proposed. It is shown that transaction creation is effective and requires almost the same resources as multiple ElGamal encryption. In addition to ElGamal encryption of all income and expenses, an additional exponentiation operation with small exponents, representing transferred sums, is needed. AA computation resources are slightly larger, since they have to be adequate for search procedures in the small range from 1 to ${2^{32}}-1=4294967295$ for individual money transfers.

Publisher

Vilnius University Press

Subject

Applied Mathematics,Information Systems,General Medicine

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