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Liyanage, S. G. H. (2018). Monerosci: linkability and traceability analysis of monero blockchain. Unpublished Undergraduate thesis , University of Colombo. 
Added by: Rucknium (2/24/22, 9:29 PM)   
Resource type: Thesis/Dissertation
BibTeX citation key: Liyanage2018
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Categories: Monero-focused
Creators: De Zoysa, Liyanage
Publisher: University of Colombo
Views: 8/435
Attachments   2014CS078.pdf [2/315] URLs   https://dl.ucsc.cm ... dle/123456789/4202
Abstract
Cryptocurrencies are one of the most popular and valuable digital currency using as a medium for the financial transaction. There are several cryptocurrencies such as Bitcoin, Ethereum, Ripple, Litecoin, etc. But the main issue of those is the anonymity within a transaction. Considering Bitcoin, every transaction on the blockchain is broadcast publicly and visible for all entities in the network, but the owner of each wallet is unknown. Every transaction is bind with the owner’s public address. If the owner’s public address reveals the transaction’s anonymity also reveals. This is the term called pseudo-anonymity.Monero is a one of a cryptocurrency found for the solution of the problem in anonymity. Monero has a set of inbuilt privacy features than Bitcoin. Monero developers have ensured this privacy feature by addressing the main two properties. Unlinkability and untraceability. But some researchers have found some issues of Monero unlinkability and untraceability guarantees by making some attacks for the Monero. But anyone hasn’t verified or evaluate those attacks because for the Monero it has no optimized environment to analyze, explore or query the blockchain. In this dissertation, has proposed an optimized environment to explore and analyze the Monero blockchain called MoneroSci which perform queries faster than existing tools and has verified the existing traceability attacks conducted by the past researchers. And has extended the attack to analyze the linkability guarantee in Monero. During the study, it has evaluated the performance of MoneroSci Parser and Analysis Library. MoneroSci loads the whole blockchain data in 15 seconds for the analysis. And it quantified the 87% of transactions are traceable based on the attacks.
  
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