Introducing Intelligence into Your Malware Analysis

Overview

Enhance malware analysis techniques with intelligent approaches to uncover hidden threats and improve detection capabilities.

Syllabus

• Introduction to Malware Analysis
Overview of Malware Types and Behaviors
Traditional Malware Analysis Techniques
• Fundamentals of Artificial Intelligence in Cybersecurity
Introduction to AI and Machine Learning
Key AI Concepts Relevant to Malware Analysis
• Intelligent Malware Detection Techniques
Using Machine Learning for Pattern Recognition
Implementing Anomaly Detection in Malware Analysis
• Feature Engineering for Malware Analysis
Identifying Features from Malware Samples
Feature Selection and Dimensionality Reduction
• Building and Training AI Models for Malware Detection
Data Preprocessing and Labeling
Choosing and Training the Right Model (e.g., SVM, Neural Networks)
Evaluating Model Performance and Metrics
• Advanced Threat Hunting with AI
Behavioral Analysis with AI Capabilities
Leveraging AI for Real-time Threat Detection
• Case Studies and Applications
Real-world Applications of AI in Malware Analysis
Lessons Learned and Best Practices
• Ethical Considerations and Challenges
Addressing Bias and False Positives in AI Systems
Privacy Concerns and Responsible AI Use
• Hands-on Labs and Projects
Developing an AI-based Malware Detection System
Analyzing Malware Samples with AI Tools
• Future Trends in Intelligent Malware Analysis
Emerging Technologies and Techniques
The Role of AI in the Evolving Threat Landscape

Subjects

Conference Talks