Course in Ethics in AI for Cyber Defence
Online course of 300 hours in AI ethics for cyber defence. 6 modules covering AI in cyber defence, international law and cyber operations, risks of defensive AI, privacy and surveillance, governance and accountability, and a responsible AI-driven cyber defence project, with an assigned technical tutor.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Describe applications of AI in detecting and responding to cyber threats.
Analyse the international law applicable to cyber operations.
Identify risks of defensive AI such as adversarial attacks and false positives.
Balance network monitoring with privacy protection.
Assign responsibilities in automated cyber defence decisions.
Apply security and AI risk management frameworks.
Design a responsible AI-supported cyber defence project.
Who it's for
- Cyber defence analysts.
- Machine learning security engineers.
- Security operations centre (SOC) analysts.
- Cybersecurity legal advisers.
- Privacy officers.
- AI security researchers.
- Engineering or science graduates aiming to enter cybersecurity.
What you'll work with
- Tallinn Manual 2.0 (international law applicable to cyber operations, 2017)
- Directive (EU) 2022/2555 (NIS2, network and information security)
- Regulation (EU) 2024/1689 (Artificial Intelligence Act)
- Budapest Convention on Cybercrime (2001)
- Law 36/2015 (Spanish National Security Act)
- ISO/IEC 27001 (information security management)
- NATO Principles of Responsible Use of AI (2021)
- Splunk
- Elastic Security
- MITRE ATLAS
- Python (scikit-learn)
6 modules · 300 h
1.1Intrusion detection with machine learning1.2Malware analysis and classification1.3Augmented SOC and SOAR orchestration1.4Automated threat intelligence1.5Active cyber defence and offensive operations1.6Language models in cybersecurity1.7Dual use of AI tools1.8Ethical framework for cyber defence1.9NATO Principles of Responsible Use of AI1.10Case study: deploying AI in an operations centre
2.1Tallinn Manual 2.02.2Sovereignty, non-intervention and the use of force2.3Cyber operations and international humanitarian law2.4Distinction and proportionality in cyberspace2.5Voluntary norms of the UN GGE2.6Attribution and proportionate response2.7Countermeasures and self-defence2.8Protection of civilian critical infrastructure2.9Hospitals and essential services2.10Case study: analysis of the NotPetya attack
3.1False positives and blocking of legitimate services3.2Adversarial attacks on detectors3.3Training data poisoning3.4Automatic escalation and autonomous response3.5Human oversight of automated responses3.6Explainability for analysts3.7Bias in automated attribution3.8Reliability of language models3.9MITRE ATLAS threats to AI systems3.10Lab: evading a malware classifier
4.1Deep packet inspection and privacy4.2Employee monitoring and proportionality4.3GDPR and processing for security purposes4.4The NIS2 Directive and its obligations4.5Log retention4.6Intelligence sharing and personal data4.7Mass surveillance under the pretext of cyber defence4.8Spyware and the Pegasus case4.9Judicial safeguards and oversight4.10Case study: proportionality assessment of a monitoring platform
5.1Spanish National Cybersecurity Strategy5.2Joint Cyberspace Command and CCN-CERT5.3Responsible vulnerability disclosure5.4Vulnerability stockpiling and the EternalBlue case5.5The exploit market and its regulation5.6Export controls on intrusion software5.7Ethical hackers and bug bounties5.8Ethics training for analysts5.9Accountability for operations5.10Workshop: vulnerability disclosure policy
6.1Definition of the defensive AI system6.2Threat analysis and use cases6.3Technical risk assessment6.4Privacy and proportionality analysis6.5Design of human oversight6.6Applicable legal framework6.7Testing and audit plan6.8Monitoring indicators6.9Report and presentation6.10Final project: final review with the tutor
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so you can combine it with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Splunk, Elastic Security, MITRE ATLAS and Python (scikit-learn), in free, academic or evaluation versions. Practice is based on real procedures: AI-based intrusion detection labs, case analyses of cyber operations and privacy assessments of monitoring systems. Assessment is continuous by module, plus the final project.
Standards covered: Tallinn Manual 2.0 (2017), Directive (EU) 2022/2555 (NIS2), Regulation (EU) 2024/1689 (AI Act), Budapest Convention on Cybercrime (2001), Law 36/2015 on National Security, ISO/IEC 27001, NATO Principles of Responsible Use of AI (2021).
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- No prior qualification is required.
- Internet connection and a computer capable of running the programme software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 300 hours over 3 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Splunk, Elastic Security, MITRE ATLAS and Python (scikit-learn), using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute certificate, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
No prior qualification is required; you need a computer able to run the programme software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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