Overview
Explore innovative AI-driven web security methods, including facial recognition for 2FA, user behavior analysis, and machine learning to detect fraudulent content, enhancing protection for all users.
Syllabus
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- Introduction to AI in Web Security
-- Overview of AI technologies
-- Importance of AI in modern web security
- Facial Recognition for Two-Factor Authentication (2FA)
-- Basics of facial recognition technology
-- Implementing facial recognition in 2FA systems
-- Privacy concerns and ethical considerations
- User Behavior Analysis
-- Understanding user behavior analytics (UBA)
-- AI techniques for behavioral profiling
-- Case studies: Successful implementations of UBA
- Machine Learning for Fraud Detection
-- Introduction to machine learning fundamentals
-- Building models to identify fraudulent content
-- Evaluating model performance and refining algorithms
- Integrating AI with Traditional Security Measures
-- Combining AI tools with existing security frameworks
-- Enhancing security protocols with AI-driven insights
- Challenges and Limitations of AI in Web Security
-- Limitations of current AI technologies
-- Addressing false positives and other common issues
-- Ethical implications and regulatory concerns
- Future Trends and Developments in AI-based Security
-- Emerging technologies and innovations
-- The evolving landscape of cyber threats
-- Preparing for the future of AI in web security
- Conclusion and Course Review
-- Recap of key learnings
-- Practical applications and future learning opportunities
Taught by
Tags
On-Demand
