ENGINEERING PATTERNS IN CYBERSECURITY DRIVEN BY AI
Hardik A. Vyas · International Journal of Cyber Warfare and Terrorism · 2025
Over time, "Artificial Intelligence (AI)" has become an increasingly important component in the field of Cybersecurity.The ability of artificial intelligence to detect, prevents, and manages cyber hazards have the potential to bring about a profound transformation in the way that businesses operate."Machine Learning (ML) models" and other AI-driven solutions are able to swiftly evaluate huge volumes of data, therefore detecting patterns and abnormalities that may be difficult for humans to observe.Anomaly detection, behavioural analysis, and predictive analytics are some of the strategies that are utilised by these systems in order to improve threat identification.As a consequence of this, elaborate attacks such as "Advanced Persistent Threats (APTs)" could be identified more quickly and efficiently.The capability of artificial intelligence to automate event reaction is a crucial aspect of this artificial intelligence.The amount of time needed to notice a cyber assault and put in place steps to mitigate its impacts is cut down as a result of this process.While artificial intelligence does improve Cybersecurity, it also generates new vulnerabilities at the same time.Data poisoning and model evasions are two examples of recent adversarial attacks.These attacks include malicious actors using "AI models" to trick security systems or offer incorrect results.The application of "Artificial Intelligence (AI)" is increasing the social engineering techniques, phishing schemes, and malware creation activities of criminals.As a result of the ongoing arms race in Cybersecurity, robust frameworks are absolutely necessary for the protection of "Artificial Intelligence (AI)" systems.