Enhancing Rely On the Cryptocurrency Market: A Track Record Scoring Method

I have actually simply completed my Master of Science in Data Science program at SMU. One of the requirements of this program was to complete a research task called a Capstone project, sort of like a thesis however a bit different. Partnering with 2 other trainees and two outdoors advisors, we completed the job. We picked to research rely on cryptocurrency. We came up with what we think can be the structure for improving trust in the cryptocurrency marketplace. Producing a reputation score for each user can provide more reliable deals while still keeping the anonymity of the users. Below is the abstract of our paper.

Trust is paramount for the efficient operation of any financial system. While the dispersed architecture of blockchain innovation on which cryptocurrencies run has numerous advantages, the privacy of users on the blockchain has provided criminal users an opportunity to conceal both their identities and illegal activities. In this paper, we provide a scoring mechanism for cryptocurrency users where ball games represent users’ credibility as safe or dangerous transactors in the cryptocurrency community. In order to distinguish law-abiding users from possible dangers in the Bitcoin market, we analyze historic thefts to profile transactions, categorize them into risky and non-risky categories utilizing numerous artificial intelligence strategies, and finally determine a reputation rating for every single unique user based upon their past association with any illegal Bitcoin incident. The Support Vector Machine design based upon two key characteristics produces a precision of 86% and is thought about the most appropriate for our dataset. Our credibility rating ranges from 0 to the overall number of transactions by a provided user where a higher rating indicates greater credibility in making Bitcoin deals. This score assists to recognize trusted users and, therefore, acts as a guideline for safe Bitcoin deals. In the cryptocurrency marketplace, our self-attestation metric through a track record score uses a foundation for boosting trust between negotiating parties.If you are interested in our work, below is the connect to our paper. Also, please leave some remarks and let us understand your ideas on our work! https://scholar.smu.edu/datasciencereview/vol1/iss3/5/

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