Developing Quantum-Enhanced Privacy-Preserving Artificial Intelligence Frameworks Based on Physical Principles to Protect Sensitive Government and Healthcare Data from Foreign Cyber Threats

Abstract

The rising cases of cyber threats to sensitive government and healthcare information has forced newer and stronger systems of data protection. Conventional encryption protocols, though efficient, are losing their effectiveness due to the enhanced cyber-attacks especially by foreign enemies. The paper examines how quantum enhanced, privacy aware Artificial Intelligence (AI) systems, whose framework is supported by physical concepts, can be used to protect important data. We suggest a combination of quantum computing as a way to achieve increased security and AI-based, privacy-protective methods, including federated learning and blockchain. The quantum nature makes sure the data is encrypted and computed in a manner that cannot be easily broken using the common cryptographic mechanisms, and AI makes the most out of the situation and adjusts to evolving threats on the fly. By building these structures, we would like to develop a model that will easily prevent unauthorized access, and address the risks posed by external cyber threats. The possible uses of these quantum-enhanced AI systems in governmental and healthcare data are also discussed in the paper, providing the effectiveness of such systems in not only sharing data safely but also predicting a risk in real time. The new method offers a bright way out of the current fight against the advanced cyber attacks of the sensitive information.