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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 ****