Enhancing Cryptocurrency Security and Trend Prediction Using XGBoost: An AI-Driven Approach
Year: 2025
Type: article
Abstract: Cryptocurrency, a digital currency secured by cryptography, has soared in popularity since the introduction of Bitcoin in 2009. While offering benefits like decentralization and faster transactions, it also faces challenges such as security threats and market volatility. Artificial intelligence (AI) presents a promising solution to enhance security and predict trends in the cryptocurrency market. This thesis explores how AI can be utilized to strengthen the security of cryptocurrency transactions and predict market trends. By analyzing current security measures, AI-driven approaches, and predictive models, this study aims to contribute to the development of innovative solutions for navigating cryptocurrency.
Author: Kamma, Shrenik
Institution: Bryant University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7000162066
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