Strategic Integration of AI in Modern Cybersecurity Frameworks

Le résumé fourni par la source

The rapid advancements in Artificial Intelligence (AI) have significantly transformed the landscape of cybersecurity, providing both new opportunities and challenges. This chapter explores the dynamic interplay between AI and cybersecurity, focusing on how AI-driven solutions enhance threat detection, incident response, and risk mitigation while also examining the emerging threats posed by AI-powered cyberattacks. AI has revolutionized cybersecurity by enabling intelligent automation, real-time threat analysis, and predictive modelling. Machine learning algorithms can detect anomalies, identify malware patterns, and adapt to evolving attack strategies, making cybersecurity defences more proactive and efficient. Deep learning techniques further enhance Intrusion Detection Systems (IDS), enabling faster and more accurate identification of potential security breaches. Additionally, AI-powered security frameworks strengthen authentication mechanisms, fraud detection, and vulnerability management, reducing human errors and response time. However, AI itself is a doubleedged sword in cybersecurity. While it strengthens defences, cybercriminals increasingly leverage AI to develop sophisticated attack methods, including adversarial AI, deepfake-based social engineering, and automated hacking tools. The rise of AIdriven cyber threats demands an equally robust AI-driven defence mechanism, necessitating the development of explainable AI (XAI) for transparent decision-making and ethical AI governance to prevent misuse. This chapter provides a comprehensive analysis of AI’s role in cybersecurity, discussing real-world applications, challenges, and future trends. It also highlights the ethical and regulatory considerations in deploying AI-based security solutions. By addressing these aspects, this chapter aims to provide a balanced perspective on harnessing AI’s potential to build a resilient cyber-security framework while mitigating the risks associated with its adversarial applications.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.