This chapter explores the technical foundations of modern cybersecurity, emphasizing the integration of artificial intelligence (AI) and machine learning (ML) to combat evolving threats. As cyber threats become more sophisticated, attackers leverage techniques like ransomware-as-a-service (RaaS), supply chain attacks, and AI-powered malware to bypass traditional defenses. Additionally, the potential of quantum computing to break current encryption standards poses a significant future risk. The chapter begins with an in-depth examination of cybersecurity architecture, covering traditional models like the confidentiality, integrity, and availability (CIA) triad and advanced frameworks. It then introduces key security protocols and cryptographic methods, including RSA encryption and Diffie-Hellman key exchange, alongside practical examples and mathematical foundations. The discussion extends to malware analysis, exploitation techniques, and mitigation strategies, incorporating models like epidemic modeling and CVSS scoring. The latter section focuses on AI-driven cybersecurity frameworks, such as defense-in-depth and zero trust models, AI’s role in incident response, and the automation of security operations. By merging AI with foundational cybersecurity principles, this chapter provides a structured approach to addressing modern cyber threats, ensuring a proactive and resilient defense strategy.