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On Efficient Transaction Anonymization Methods in Blockchain
PhD Thesis Proposal Defence Title: "On Efficient Transaction Anonymization Methods in Blockchain" by Mr. Wangze NI Abstract: Due to its remarkable attributes such as transparency, immutability, and decentralization, blockchain technology has been gaining significant attention. However, transparency also gives rise to privacy concerns, presenting a dual-edged nature. Researchers have proposed some privacy protection methods. Nonetheless, the efficiency of these methods still requires improvement. In this proposal, I focus on enhancing the efficiency of two promising privacy protection approaches for transaction amounts: mixing methods and payment channel networks. Specifically, mixing methods mix several transactions into one mixing transaction and decompose each original output in original transactions into a set of decomposed outputs. As a result, there are multiple decomposed outputs with identical values originating from different transactions. A payment channel network is a collection of off-chain payment channels. Users can tract in payment channels, and the details of each transaction in a payment channel is only known to its participants. My first work focus on minimizing the number of decomposed outputs in a mixing transaction with required anonymity. I define a novel concept, namely a c-decomposition, and prove its anonymity. Besides, I define the anonymity-aware output decomposition (AA-OD) problem, which aims to find a c-decomposition with a minimal size. I prove that AA-OD is NP-hard. To solve AA-OD, I propose an approximation algorithm, namely Boggart. My second work focus on efficiently obtaining a rebalance solution to effectively increase the success ratio of the transactions (SRoT) in a payment channel network. I define the utility of a rebalance transaction and the utility-aware rebalance (UAR) problem. To maximize the effect of improving SRoT, UAR aims to find a set of transactions with maximized utilities. I prove UAR is NP-hard and cannot be approximately solved with a constant ratio. Thus, I propose two heuristic algorithms, namely Circuit Greedy and UAR_DC. Date: Friday, 3 November 2023 Time: 3:00pm - 5:00pm Venue: Room 5510 lifts 25/26 Committee Members: Prof. Lei Chen (Supervisor) Dr. Dimitris Papadopoulos (Chairperson) Dr. Shuai Wang Prof. Ke Yi **** ALL are Welcome ****