Securing the Web with AI

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

• 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

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Subjects

Conference Talks