The Invisible Defence
Debojyoti Gupta · 2025
Zero-day threats are one of the most challenging issues in cybersecurity today because they exploit vulnerabilities that are unknown to security professionals. This chapter delves into the “Invisible Defence,” a strategy that utilizes artificial intelligence (AI) to detect and counteract these hidden threats before they cause harm. By analyzing behavior patterns and predicting potential exploits, AI offers a proactive approach to cybersecurity that traditional methods lack. We explore several real-world case studies and success stories where AI has effectively identified and mitigated zero-day threats. These examples illustrate AI’s capacity to adapt to new and unforeseen challenges, providing a dynamic defence mechanism that evolves with emerging threats. This chapter also examines the limitations of conventional security measures, such as signature-based detection, and how AI can fill these gaps by learning and improving over time. Additionally, we discuss the technical foundations of AI in cybersecurity, including machine learning algorithms and neural networks, and how they are applied to detect anomalies and potential threats. The role of data in training these systems is also highlighted, emphasizing the importance of large datasets in improving AI’s accuracy and efficiency. This research aims to provide a comprehensive understanding of AI’s role in modern cybersecurity strategies, showcasing how it can enhance our defences against the ever-present danger of zero-day threats. By integrating AI into cybersecurity frameworks, we can build more resilient systems that not only react to threats but also anticipate and neutralize them before they become critical issues.