|

Course Overview

Cyber threats are growing in frequency, complexity, and sophistication, often outpacing traditional defense systems. AI-powered threat intelligence combines machine learning, natural language processing, and predictive analytics to provide real-time monitoring, automated detection, and strategic foresight into malicious activity.

Delivered by EuroQuest International Training, this ten-day course explores how AI transforms cyber threat intelligence—covering data collection, anomaly detection, threat attribution, adversarial AI risks, and governance. Participants will analyze global case studies of AI-driven defense, explore ethical and legal considerations, and learn to align AI systems with organizational security strategies.

The course balances technical depth with strategic insights, ensuring participants gain a comprehensive view of how AI enhances cybersecurity intelligence.

Course Benefits

• Leverage AI and machine learning for proactive threat detection

• Build cyber threat intelligence systems powered by automation

• Anticipate and mitigate risks of advanced persistent threats (APTs)

• Strengthen governance and oversight of AI-driven cybersecurity

• Apply global best practices in AI and cyber defense integration

Why Attend

This course prepares leaders to transform cybersecurity into a foresight-driven function. By mastering AI-powered threat intelligence, participants can secure their organizations against advanced attacks, reduce response times, and protect critical assets.

Training Methodology

• Structured knowledge sessions

• Strategic discussions on AI in cybersecurity

• Case illustrations of AI-driven threat intelligence

• Scenario-based exploration of cyber risks

• Conceptual frameworks and foresight planning

Course Objectives

By the end of this training course, participants will be able to:

• Define the role of AI in cyber threat intelligence systems

• Apply machine learning models for anomaly detection

• Integrate AI into threat intelligence platforms (TIPs and SIEMs)

• Assess risks of adversarial AI and data poisoning attacks

• Use AI for predictive threat modeling and attribution

• Strengthen governance in AI-driven cybersecurity systems

• Evaluate global best practices in AI threat defense

• Align AI cybersecurity with legal and ethical frameworks

• Build resilient systems for continuous monitoring

• Apply foresight to anticipate next-generation cyber threats

Course Outline

Unit 1: Introduction to Cyber Threat Intelligence

• Principles of cyber threat intelligence (CTI)

• Evolution of threats in digital ecosystems

• AI’s role in transforming cybersecurity

• Governance and accountability in CTI

• Case perspectives in cyber intelligence

Unit 2: AI and Machine Learning in Cybersecurity

• Fundamentals of AI and ML in cyber defense

• Supervised and unsupervised models for threat detection

• Natural language processing for dark web monitoring

• Predictive analytics in security systems

• Case studies of AI in defense

Unit 3: Threat Data Collection and Processing

• Gathering structured and unstructured threat data

• Integrating global threat feeds

• Automated data classification and enrichment

• Governance in data-driven cybersecurity

• Lessons from intelligence platforms

Unit 4: AI for Anomaly and Intrusion Detection

• Detecting zero-day attacks with AI

• AI in intrusion detection and prevention systems

• Behavioral analytics of users and entities (UEBA)

• Case perspectives in anomaly detection

• Reducing false positives with AI

Unit 5: Threat Attribution and Response Automation

• AI in identifying threat actors and patterns

• Attribution challenges in cyber defense

• Automated incident response systems

• AI in security orchestration (SOAR platforms)

• Case illustrations in automated response

Unit 6: Risks of Adversarial AI

• Adversarial machine learning attacks

• Data poisoning and evasion techniques

• Risks of over-reliance on AI models

• Mitigation frameworks for adversarial risks

• Governance and accountability in AI security

Unit 7: AI and Cloud/IoT Cybersecurity

• AI in securing cloud ecosystems

• IoT threat intelligence frameworks

• Real-time monitoring of distributed networks

• Predictive AI for IoT vulnerabilities

• Global case studies in cloud/IoT security

Unit 8: Legal, Ethical, and Policy Frameworks

• Legal implications of AI-driven intelligence

• Data protection and privacy challenges

• Ethical dilemmas in automated decision-making

• Global regulatory perspectives (GDPR, NIS2, etc.)

• Governance for responsible AI in cybersecurity

Unit 9: Strategic Foresight in Cyber Threat Intelligence

• Anticipating emerging cyber risks

• Scenario planning for future attacks

• AI foresight in geopolitical and state-sponsored threats

• Designing resilient cyber intelligence strategies

• Lessons from foresight-driven organizations

Unit 10: Case Studies in AI-Powered Threat Intelligence

• AI applications in banking and finance security

• AI in critical infrastructure protection

• Lessons from government and defense sectors

• Sector-specific applications of AI CTI

• Strategic takeaways for executives

Unit 11: Building AI-Driven CTI Systems

• Designing AI-powered threat intelligence platforms

• Integrating AI with SIEM and SOC operations

• KPIs for AI cyber threat intelligence systems

• Continuous monitoring and adaptive learning

• Case perspectives in enterprise adoption

Unit 12: Designing Sustainable AI Cybersecurity Frameworks

• Institutionalizing AI in security governance

• KPIs for monitoring AI-driven intelligence performance

• Continuous improvement and system resilience

• Embedding foresight in AI-powered defense

• Final consolidation of insights

Target Audience

• CISOs and cybersecurity executives

• Threat intelligence and SOC professionals

• Risk, governance, and compliance leaders

• IT managers and digital security specialists

• Policy and regulatory professionals in cybersecurity

Target Competencies

• AI and ML for cyber threat intelligence

• Anomaly detection and predictive modeling

• Governance and compliance in AI security

• Adversarial AI and risk mitigation

• Threat attribution and automated response

• Global perspectives on AI cybersecurity

• Strategic foresight in threat intelligence

Join the AI-Powered Cyber Threat Intelligence Training Course from EuroQuest International Training to master advanced frameworks, governance models, and foresight strategies that transform AI into a decisive tool for cybersecurity resilience.