Intelligent Resource Allocation in Platforms for Cybersecurity Enabled by AI

Abstract

Rising complexity of assaults in the evolving terrain of cybersecurity requires the adoption of advanced technologies. Particularly in the coordination of systems combining many security technologies and practices, artificial intelligence (AI) has become a critical tool for raising the performance of cybersecurity systems. A main challenge for these systems is the intelligent allocation of resources to assure optimal performance while reducing expenses. This paper explores the concept of intelligent resource allocation in AI-enabled cybersecurity orchestration systems with a focus on how AI approaches may be used to dynamically allocate resources, prioritize operations, and respond to evolving dangers in real-time. We study in resource management the applications of predictive analytics, machine learning algorithms, and decision-making models by way of an examination of present literature. We also discuss the challenges and future possibilities in using artificial intelligence-driven resource allocation methods including assurances of scalability, resolution of latency issues, and system resilience. Emphasizing the probable benefits of artificial intelligence in improving the flexibility and efficiency of cybersecurity systems, the paper provides analysis on the integration of many technologies for improved resource usage.