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- Creators: Computer Science and Engineering Program
Description
Third-party mixers are used to heighten the anonymity of Bitcoin users. The mixing techniques implemented by these tools are often untraceable on the blockchain, making them appealing to money launderers. This research aims to analyze mixers currently available on the deep web. In addition, an in-depth case study is done on an open-source bitcoin mixer known as Penguin Mixer. A local version of Penguin Mixer was used to visualize mixer behavior under specific scenarios. This study could lead to the identification of vulnerabilities in mixing tools and detection of these tools on the blockchain.
ContributorsPakki, Jaswant (Author) / Doupe, Adam (Thesis director) / Shoshitaishvili, Yan (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Bitcoin is a form of virtual currency that can be used as a medium of exchange for goods or services. Different from other forms of virtual payment, bitcoin is de-centralized and puts all of the power in the hands of the user, rather than a banking institution. However, bitcoin's ability to develop as a renowned medium of exchange has been impeded, potentially due to a lack of knowledge, active bitcoin platforms, and support. In this paper, I conduct a survey to understand factors that affect households' adoption of bitcoin. In particular, I focus on factors that capture the potential benefit and cost of adopting bitcoin. Through a public survey, participants are asked a series of questions on their willingness to adopt bitcoin. I found significant results stating that subjects were more inclined toward bitcoin contingent upon the number of platforms accepting it, the number of acquaintances using bitcoin, and the degree of personal knowledge participants have about bitcoin. These findings suggest that perceived benefit captured by network effect and convenience of use, as well as the potential cost captured by uncertainty help shape the adoption of bitcoin.
ContributorsMorrissey, Michael Joshua (Author) / Wang, Jessie (Thesis director) / Ray, Colter (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
In this paper I defend the argument that public reaction to news headlines correlates with the short-term price direction of Bitcoin. I collected a month's worth of Bitcoin data consisting of news headlines, tweets, and the price of the cryptocurrency. I fed this data into a Long Short-Term Memory Neural Network and built a model that predicted Bitcoin price for a new timeframe. The model correctly predicted 75% of test set price trends on 3.25 hour time intervals. This is higher than the 53.57% accuracy tested with a Bitcoin price model without sentiment data. I concluded public reaction to Bitcoin news headlines has an effect on the short-term price direction of the cryptocurrency. Investors can use my model to help them in their decision-making process when making short-term Bitcoin investment decisions.
ContributorsSteinberg, Sam (Author) / Boscovic, Dragan (Thesis director) / Davulcu, Hasan (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05