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Integration of LLMs With Traditional Security Tools
Abstract
The integration of large language models (LLMs) with traditional security tools represents a significant advancement in the cybersecurity domain. This chapter explores the potential of combining LLMs with established security mechanisms to enhance threat detection, response, and overall system resilience. By analyzing the complementary strengths of LLMs and traditional tools, this chapter highlights how LLMs can augment existing security frameworks, improve anomaly detection, automate security workflows, and address evolving cyber threats. The discussion also includes challenges such as computational complexity, ethical considerations, and integration complexities, offering insights into future research directions.
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