Word count: 5000 words
Objectives to cover:
Introduction: Overview of cybersecurity challenges and the need for intelligent intrusion detection.
Background: Motivation behind integrating AI and LLMs in cybersecurity frameworks.
Literature Review: Summary of existing IDS and AI-based security approaches.
Intrusion Detection Systems (IDS): Core concepts, types, and functionalities of IDS.
AI in Cybersecurity: Role of machine learning and LLMs in threat detection.
Proposed Framework Architecture: Design of the LLM-powered intrusion detection and response system.
Autonomous Incident Response: Mechanisms for automatic threat mitigation and response.
Implementation and Evaluation: Dataset, experiments, simulation results, and performance metrics.
Conclusion: Summary of findings, contributions, and future directions.
Reference: IEEE Style