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(UPI) Chapter 19: AI in Cybersecurity Course (How To)

32-minute College Credit course: Chapter 19 explores how AI, particularly deep learning models like RNNs and CNNs, enhances malware detection by an...
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Overview

Chapter 19 explores how AI, particularly deep learning models like RNNs and CNNs, enhances malware detection by analyzing static and dynamic features, addressing the growing complexity of cyber threats with automated precision.

Syllabus

  • Introduction to AI in Cybersecurity
  • Overview of AI applications in cybersecurity
    The role of AI in addressing cyber threats
    Advantages and limitations of AI-based cybersecurity
  • Deep Learning Models in Cybersecurity
  • Introduction to Recurrent Neural Networks (RNNs)
    Introduction to Convolutional Neural Networks (CNNs)
    Comparison between RNNs and CNNs for cybersecurity tasks
  • Malware Detection with AI
  • Static feature analysis for malware detection
    Dynamic feature analysis for malware detection
    Improving detection accuracy with ensemble learning
  • Implementing RNNs for Cyber Threat Detection
  • Building RNN models for sequence-based data in cybersecurity
    Training and evaluating RNNs on cybersecurity datasets
    Case studies on RNN applications in malware detection
  • Implementing CNNs for Cyber Threat Detection
  • Utilizing CNNs for image-based security data analysis
    Training and evaluating CNNs on cybersecurity datasets
    Case studies on CNN applications in intrusion detection
  • Addressing the Complexity of Cyber Threats
  • Challenges in detecting sophisticated cyber threats
    Role of AI in adapting to new and evolving threats
    Strategies to improve AI precision in threat detection
  • Automation in Cyber Defense
  • Building automated response systems with AI
    Integrating AI with existing security infrastructure
    Impact of AI automation on incident response time
  • Ethical and Security Considerations
  • Ethical implications of using AI in cybersecurity
    Security risks associated with AI models
    Best practices for securing AI systems against adversarial attacks
  • Future Trends in AI and Cybersecurity
  • Emerging AI technologies in cyber defense
    Predicting future cyber threats with AI
    Innovations in AI to enhance cybersecurity resilience
  • Conclusion and Course Wrap-up
  • Review of key concepts
    Discussion on the future of AI in cybersecurity
    Final thoughts and further reading resources

Subjects

Information Security (InfoSec)