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Stream/Area:
-
Subject:
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Paper ID:
IJSREM60745
Volume:
10 |
4 |
April 2026
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Cryptocurrency trading has rapidly evolved into a highly dynamic and technology-driven financial domain, attracting significant attention from investors, researchers, and institutions worldwide. This paper presents a comprehensive review of modern cryptocurrency trading platforms by combining blockchain technology, artificial intelligence, and advanced trading mechanisms to create a secure, efficient, and scalable trading ecosystem. The study highlights the use of deep learning approaches such as Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and attention-based models for improving cryptocurrency price prediction. These techniques utilize technical indicators, trading patterns, and social media data to enhance prediction accuracy. In addition, reinforcement learning strategies are explored to optimize trading decisions and improve performance under highly volatile market conditions. Furthermore, the paper discusses real-time data integration using APIs, secure authentication mechanisms, and scalable system architectures required for continuous trading operations. It also examines the regulatory landscape of cryptocurrency, particularly in the Indian context, including taxation policies and emerging concepts like Central Bank Digital Currencies (CBDCs). Overall, this review provides insights into the development of intelligent, secure, and user-friendly cryptocurrency trading platforms such as CryptoVista.
KEYWORDS
Publication Date
4/20/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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