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International Journal of Scientific Research and Engineering Development( International Peer Reviewed Open Access Journal ) ISSN [ Online ] : 2581 - 7175 |
IJSRED » Archives » Volume 8 -Issue 6

📑 Paper Information
| 📑 Paper Title | Privacy-Preserving and Quantum-Enhanced AI for Sensitive Data Protection |
| 👤 Authors | Ayush Das, Anirban Mukherjee |
| 📘 Published Issue | Volume 8 Issue 6 |
| 📅 Year of Publication | 2025 |
| 🆔 Unique Identification Number | IJSRED-V8I6P163 |
| 📑 Search on Google | Click Here |
📝 Abstract
As the digital transformation accelerates across industries, the need for robust data protection mechanisms has never been more critical. Sensitive data, particularly in sectors like healthcare, finance, and government, is constantly at risk of exposure due to increasing cyber threats. Traditional encryption techniques, while effective, often fall short when dealing with large-scale data and complex threats. This paper explores the intersection of privacy-preserving techniques, quantum computing, and artificial intelligence (AI) to enhance data protection. We propose the integration of quantum-enhanced AI frameworks that combine quantum computing's unique capabilities with AI-driven privacy-preserving mechanisms. These systems can not only safeguard sensitive data but also improve the efficiency of encryption and decryption processes. The paper discusses the potential of quantum-enhanced AI in creating more secure, scalable, and transparent data protection strategies, while addressing the challenges of implementing such advanced technologies, including computational complexity and ethical considerations. By leveraging quantum algorithms and AI techniques such as homomorphic encryption and differential privacy, the proposed solution aims to provide a futureproof approach to protecting sensitive information from increasingly sophisticated threats.
📘 Other Details
