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課程時長 14 時間：
課程簡介
Introduction to Cybersecurity and LLMs
- Current landscape of cybersecurity threats
- Basics of Large Language Models
- Advantages of using LLMs in cybersecurity
LLMs for Threat Detection
- Using LLMs to analyze and interpret security logs
- Training LLMs for anomaly and pattern detection
- Case studies: LLMs in intrusion detection systems
LLMs for Security Automation
- Automating incident response with LLMs
- LLMs in phishing detection and email filtering
- Enhancing security protocols with AI
LLMs for Threat Intelligence
- Gathering and processing threat intelligence with LLMs
- LLMs for predictive threat modeling
- Sharing and disseminating intelligence with LLMs
Integrating LLMs into Security Operations
- Best practices for deploying LLMs in security operations centers
- Maintaining and updating LLMs for optimal performance
- Addressing privacy and ethical concerns
Hands-on Lab: Implementing LLMs in Cybersecurity
- Setting up a cybersecurity lab environment with LLMs
- Developing a threat detection model using LLMs
- Simulating attacks and testing model effectiveness
Summary and Next Steps
最低要求
- An understanding of cybersecurity fundamentals
- Experience with Python programming
- Familiarity with machine learning concepts
Audience
- Cybersecurity professionals
- Data scientists
- IT professionals interested in the latest AI-driven security technologies
