Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
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
Requirements
- 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
14 Hours
Testimonials (1)
This topic is better with F2F, but this online training is still handled well . The important thing is the trainees were able to have understanding of Hyperledger Indy
