Quantum Computing in Cybersecurity and LLM

Quantum computing is fundamentally transforming the cybersecurity landscape by simultaneously introducing robust defense mechanisms and sophisticated attack vectors. This paper explores the dual nature of quantum computing in cybersecurity, examining how it enhances artificial intelligence-powered malware detection systems and strengthens encryption protocols, while also enabling the development of adaptive quantum-enhanced threats such as polymorphic malware and quantum key distribution attacks. Additionally, the paper analyzes the convergence of quantum computing with Large Language Models (LLMs) and neural networks, highlighting implications for threat intelligence across social media platforms, cybersecurity operations, and open-source intelligence. Through comprehensive analysis and the proposition of quantum-resilient security frameworks, this research provides cybersecurity professionals with actionable strategies for navigating the emerging quantum computing era.