Waiting for an alert to fire is no longer a defense strategy on its own – by the time most alerts trigger, an attacker has often already been inside a network for a while. That has pushed cybersecurity teams toward threat analysis: actively studying attacker behaviour, patterns, and emerging techniques so defenses are built around what is actually coming, not just what already happened.

Offered by Arab British Fellowship Training Academy, this course develops that analytical mindset in line with UK standards – moving from threat types and detection tools, through incident investigation and risk assessment, and into the advanced techniques now needed to handle AI-driven attacks and IoT-specific threats.

Who Should Attend?

• Cybersecurity professionals in government and private-sector organisations.
• Network engineers and incident response teams who deal with cyber threats directly.
• IT staff responsible for threat analysis and protecting sensitive data.
• Students and professionals looking to specialise in cyber threat analysis.

Knowledge and Benefits

• Understand the core principles of cyber threat analysis under UK standards.
• Detect and evaluate threats using advanced tools and recognised UK methodologies.
• Turn threat data into faster, better-informed protective decisions.
• Stay ahead of emerging attack techniques, including AI-driven and IoT-specific threats.

Module 1: What Threat Analysis Covers, and What It Is Analysing

• What cyber threat analysis is and its role in building a defense strategy.
• The process of identifying and evaluating cyber threats.
• External, internal, and technical threat categories.

Module 2: Working Within UK Cybersecurity Standards

• UK regulations and frameworks such as Cyber Essentials and NCSC guidance.
• Applying these standards in threat detection and analysis.
• Why compliance with UK-specific standards strengthens overall protection.

Module 3: Tools and Techniques for Serious Analysis

• Common tools for threat detection and analysis, and how to choose the right one for the job.
• Behavioural analysis of attackers and suspicious activity.
• Using machine learning, AI, and digital forensics in threat detection.

Module 4: Spotting Advanced Threats and Emerging Patterns

• Analysing new attack vectors such as ransomware and advanced phishing schemes.
• Detecting targeted attacks and advanced persistent threats (APTs).
• Using data to recognise attack patterns and shifting trends.

Module 5: From Suspicious Activity to Confirmed Incident

• Distinguishing incidents from routine events, and recognising major security incidents.
• Initial response procedures when an incident is detected.
• Using forensic techniques to analyse logs and document evidence for investigations.

Module 6: Assessing and Reducing Cyber Risk

• Risk assessment methodologies and prioritising risks by potential impact.
• Mitigation steps and applying the principle of least privilege.
• Layered security strategies to minimise vulnerabilities.

Module 7: Detection Tools and Cross-Team Collaboration

• Intrusion Detection Systems (IDS) and SIEM tools for spotting unusual activity.
• The role of log management in real-time threat detection.
• Why cross-team coordination and sharing threat intelligence improves outcomes.

Module 8: Responding, Then Preventing a Repeat

• Building an effective incident response plan and evaluating severity.
• Communicating with internal teams and external authorities during an incident.
• Applying lessons learned to strengthen policies and enable continuous monitoring.

Module 9: What’s Next – AI-Driven Attacks and IoT Exposure

• Attacks targeting AI and machine learning systems, and the challenge of securing AI-driven infrastructure.
• Using AI and big data to strengthen threat analysis and build automated detection systems.
• Security challenges specific to connected devices and IoT networks.