LLMs for Enhancing Privacy and Data Protection in Quantum Computing Environments

Abstract

The rapid advancement of quantum computing presents both tremendous opportunities and significant challenges for cybersecurity, particularly in the realms of privacy and data protection. Traditional encryption methods face obsolescence in the quantum era, as quantum algorithms like Shor's algorithm can efficiently break widely used cryptographic schemes. Large Language Models (LLMs), with their capacity for processing and analyzing vast amounts of data, have emerged as valuable tools in addressing privacy concerns in quantum computing environments. This chapter explores how LLMs can be leveraged to enhance privacy and data protection by facilitating the development of quantum-resistant cryptographic protocols, automating threat detection, and assisting in the creation of novel security architectures tailored to quantum technologies. By examining the intersection of LLMs and quantum computing, this work highlights their potential to reshape cybersecurity strategies to ensure that data remains secure in a post-quantum world.