Unified Threat Detection Platform with AI, SIEM, and XDR - Paidy, Pavan (International Journal of Artificial Intelligence, Data Science, and Machine Learning, 2025)
Businesses face increasingly complex dangers able to bypass traditional security systems in the modern fast evolving cyberspace. Security systems' jumbled architecture often leads to isolated threat detection, slow reactions, and poor view within complex IT environments. Emerging as a vital solution to handle these challenges is a unified threat detection platform including Artificial Intelligence (AI), Security Information and Event Management (SIEM), and Extended Detection and Response (XDR). This convergence helps security teams to correlate their data across endpoints, networks, cloud services & their applications, thereby enabling faster detection, improved automation & also more effective incident response. Adaptive intelligence and behavioral analytics brought by AI help to discover anomalies & risky conduct early on. Whereas XDR improves detection & also their response across many threat sources, SIEM provides centralized log management & actual time monitoring. Taken together, they provide an anticipatory & more flexible protective mechanism. Still, the integration of these technologies brings challenges like tool interoperability, data overload, the necessity of skilled staff & their ongoing optimization. Using a single platform shortened incident response times by more than 40% & greatly improved their threat visibility & also analyst productivity, according to a case study from a financial services company. Establishing strong, future-oriented cybersecurity operations will depend on integrating their platforms powered by AI & sophisticated analytics as threats grow in their scope & also their complexity