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Performance Evaluation of LLM-Based Security Systems
Abstract
This chapter delves into the performance evaluation of large language model (LLM)-based security systems, focusing on their effectiveness, scalability, and adaptability in dynamic threat landscapes. By examining various performance metrics, including accuracy, speed, and resource utilization, the chapter provides a comprehensive analysis of how these systems compare to traditional security approaches. Furthermore, it explores the challenges of evaluating LLMs in real-world scenarios and discusses potential improvements to enhance their robustness. This evaluation aims to guide future developments in LLM-based security systems, ensuring they meet the rigorous demands of modern cybersecurity.
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