Congratulations Dr. Goshgar Can Ismayilov!

Goshgar Can Ismayilov has successfully defended his PhD thesis.

Decentralized Privacy-Preserving Collective and Multi-Objective Trading Protocols on Blockchain with Zero-Knowledge Proofs  

In this thesis, we propose decentralized privacy-preserving cryptographic protocols on blockchain with zero-knowledge proofs for three essential problems. Firstly, the privacy-preserving payment problem refers to a specific group of transactions where a source address (i.e. sender) transfers a certain amount of tokens to a destination address (i.e. receiver) while still protecting the privacy of their balances and transaction details. We extend this problem to address multi-token payments as well. Secondly, the privacy-preserving aggregation problem refers to a multi-party computation where a group of blockchain addresses (i.e. aggregators) aggregate their individual data to reach the global aggregation by still protecting the privacy of their own data. We also extend this problem to address prefix aggregation and to support for arbitrary numbers of aggregators. Thirdly, privacy-preserving multi-token bartering problem refers to a multi-party computation where a group of blockchain addresses (i.e. barterers) collectively exchanges a set of tokens in return for another set of tokens through proposing bids by still protecting the privacy of their balances and bids. We extend this problem to address multi-objective bartering using Bellman-Ford algorithm and pareto-domination. We propose the PTTS protocol for the first problem, the PVSS and PRFX protocols for the second problem and the PMTBS and zkMOBF protocols for the third problem. We analyze these protocols in terms of their scalability (as computational, communication and storage overheads) and their security (as potential attacks and reduction proofs). We perform experimental evaluation on Ethereum and Avalanche to measure blockchain gas consumption, proof generation/verification  times and proof  artifact sizes.