Analysis of the Security and Reliability of Cryptocurrency Systems Using Knowledge Discovery and Machine Learning...

Area of Science:

• Computer Science
• Artificial Intelligence
• Blockchain Technology
• Cybersecurity

Background:

• Cryptocurrencies like Bitcoin utilize blockchain for secure transaction recording.
• Artificial Intelligence (AI) offers significant potential across industries due to large data processing capabilities.
• Current AI systems lack explainability and are vulnerable to adversarial attacks, posing challenges for decision-making standards.

Purpose of the Study:

• To propose a trustworthy AI-based architecture for enhancing cryptocurrency transactions.
• To leverage decentralized blockchain features like smart contracts and trust oracles within the AI framework.
• To improve the performance, security, and transaction processing of the Bitcoin network using AI.

Main Methods:

• Development of an AI-based architecture integrating decentralized blockchain characteristics.
• Implementation of smart contracts and trust oracles for secure AI decision-making.
• Utilizing AI for decentralized consensus among AI predictors and transactional network analysis.

Main Results:

• The proposed system enables secure cryptocurrency transactions through decentralized AI consensus.
• AI-driven network analysis significantly enhances the Bitcoin network's performance and security.
• The system demonstrated highly accurate output compared to existing state-of-the-art methods.

Conclusions:

• The integration of AI with blockchain offers a robust solution for secure and efficient cryptocurrency transactions.
• The proposed architecture addresses AI explainability and adversarial attack vulnerabilities.
• This approach shows promise for advancing the security and performance of blockchain-based financial systems.