- Kamilia Amdouni
- Women in Cyber ITU
- Janina Kempf
Introductory
Does this course have any restrictions?
Event Organizer(s)
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Description
The objective of Her CyberTracks is to promote the equal, full, and meaningful representation of women in cybersecurity. To this end, the training course initiative equips women with the necessary skills and mindsets to succeed in cybersecurity through targeted cyber capacity building.
Her CyberTracks offers a one-stop curriculum based on three pillars:
- TRAIN: Develop capacity to contribute to a secure and resilient cyberspace. We provide expert training courses, delivered online and on-site, to equip women with the technical and soft skills needed to shape cybersecurity
- MENTOR: Promote awareness and knowledge sharing of best practices in cybersecurity career development. We provide a platform for senior cyber professionals to mentor women at junior level and foster their professional and personal growth
- INSPIRE: Positive role models in cybersecurity inspire and empower further women to actively participate and lead in the field. We organize inspirational keynote webinars, regional networking meetings and study visits to shift perceptions and (rightly) position women as valuable additions to the cybersecurity workforce
- NETWORK: We organise networking events to establish resilient connections amongst cybersecurity experts within and across the regions
The curriculum includes the Her CyberTracks regional training, composed of on-site activities featuring soft skills masterclasses, simulations and hands-on exercises, mentorship circles, study visits to cybersecurity organisations, and engaging networking opportunities.
Participants may choose among four available CyberTracks: Policy & Diplomacy CyberTrack, Incident Response CyberTrack, Criminal Justice CyberTrack and Cyber & AI CyberTrack.
Who is eligible to participate:
The Her CyberTracks programme is being offered specifically to women residing in target countries in Africa and Arab States.
Target countries from the Africa: Angola, Benin, Botswana, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Congo, Congo (Dem. Rep), Côte d’Ivoire, Egypt, Equatorial Guinea, Eritrea, Ethiopia, Gambia, Ghana, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Rwanda, São Tomé and Príncipe, Senegal, Seychelles, Sierra Leone, South Africa, South Sudan, Tanzania, Togo, Uganda, Zambia, Zimbabwe.
Target countries from the Arab States: Algeria, Djibouti, Comoros, Libya, Mauritania, Somalia, Tunisia.
Target audience for the Cyber & AI CyberTrack: Women working in policy fields, e.g. cybersecurity, ICT/digital affairs, peace & security; and/or women in technical roles in cybersecurity interested in AI/Cyber policy and governance.
- Participants must have a minimum of 2-3 years’ experience in the fields of policymaking or diplomacy, preferably in the fields of technology, cybersecurity and/or peace and security, or in technical cybersecurity fields;
- Participants must have a good working knowledge of English (main language of delivery and of the training materials). Willingness and ability to allocate circa 15 hours per month across six months;
- Access to stable Internet connection;
- There are no age restrictions.
Upon completion of this course, participants will be able to:
- Outline the fundamentals and key concepts of AI and their impact on cybersecurity
- Analyze the risks and opportunities presented by AI in the cybersecurity landscape
- Evaluate existing and emerging policies and regulations related to cybersecurity and AI
- Apply cybersecurity and AI frameworks to assess organization’s readiness
- Develop diplomatic and communication strategies to address international cooperation on cybersecurity and AI issues
- Contribute to the development of responsible, rule-based AI frameworks for cybersecurity
- Employ anticipatory governance through scenario planning, as the role of AI in cybersecurity is fast-changing
- Evaluating cybersecurity readiness of critical infrastructure in the era of AI
The training approach incorporates a blend of self-paced and interactive learning methodologies to effectively achieve the training objectives:
- Self-paced courses: Participants will watch self-paced video presentations covering theoretical frameworks. This allows individuals to digest the content at their own pace, fostering a foundational understanding of key concepts;
- Live instructor-led Zoom sessions: Complementing self-paced learning, live instructor-led Zoom sessions offer interactive opportunities for participants. These sessions will delve deeper into the material, facilitating discussions, regional case studies, and reflective exercises. Exact day and time of the sessions will be communicated in due time, however, please note that they will be in GMT+1 time zone. Recordings will be made available. These will be followed by mandatory forum contributions;
- Face-to-face simulations and group exercises: To reinforce theoretical knowledge and practical skills, face-to-face simulations and group exercises will be conducted. This hands-on approach enables participants to apply their learning in real-world scenarios, promoting collaborative learning and skills’ development.
- Mentorship: Mentorship by subject matter experts will be available to provide guidance, support, and personalized feedback throughout the training journey.
The assessment methods for measuring the achievement of learning objectives encompass a combination of knowledge assessments and practical evaluations:
- Quizzes: Following each self-paced module, participants will undertake a quiz to gauge their comprehension of the theoretical frameworks and content covered. These quizzes will contribute to assessing the understanding of key concepts and principles;
- Mandatory forum contribution following each online instructor-led sessions;
- Active participation to mentorship sessions;
Face-to-Face Simulations and Group Exercises: The practical application of learned concepts during face-to-face simulations and exercises will be evaluated using a structured evaluation framework. Participants' performance in these hands-on activities will be assessed based on predefined criteria, such as problem-solving ability, decision-making skills, and teamwork. The weights assigned to these evaluations will reflect their significance in demonstrating competency and skill mastery.
The grading matrix will allocate weights as follows:
Face-to-face
- Online self-paced and instructor-led courses 40%
- Active participation to mentorship sessions 20%
- Face-to-face simulations and group exercises 40%
Online
- Online self-paced and instructor-led courses 60%
- Active participation to mentorship sessions 40%
A total score higher than 70% is required to obtain the ITU Certificate.
Module 1: AI Fundamentals for Cyber Professionals
- Foundational knowledge of Ai's relevance in cybersecurity focusing on its capabilities, limitations
- Outline key AI concepts, evaluating claims about AI
Module 2: AI Threats and Opportunities
- Analyze AI threats and their types
- Identify novel vulnerabilities that AI introduces into government networks that need different approaches (e.g., using commercial LLMs)
- Explain the expanded attack surface on the system (data, model, API) and societal level (disinformation)
- Describe the implications of technological AI development for the offense-defense balance in cybersecurity
- Characterize the technical capabilities of AI for threat intelligence, anomaly detection and automated incident response
Module 3: Governing Cyber and AI
- Compare different national cybersecurity governance approaches in their consideration of AI
- Detail the key policy debates surrounding AI regulation, such as data privacy and governance, algorithmic transparency, and accountability, and their intersection with cybersecurity
- Explain if and how cybersecurity governance approaches (such as NIS-2) consider AI and how they potentially could consider AI
Module 4: AI and Cyber Diplomacy
- Examine why multilateralism and international governance of AI in cybersecurity is critical
- Review the multilateral frameworks for Global AI and Cybersecurity Governance
- Contrast the different perspectives on AI governance among nations
- Develop strategies for building trust and cooperation in cyberspace
Module 5: The Cyber Horizon – AI Threats and Strategic Foresight
- List the benefits and limitations of strategic foresight methodologies as a tool in policymaking
- Summarize the basic methods for performing a strategic foresight
- Assess future trends in cybersecurity and AI incl. quantum technologies, autonomous cyber attacks
Module 6: Cyber Readiness and Critical Infrastructure
- Identify and assess sector-specific AI risks
- Evaluate national readiness to address AI-driven cyber threats through assessment of workforce skills, institutional coordination, and public–private collaboration mechanisms
- Develop policy recommendations and action plans to strengthen national preparedness for AI-enabled cybersecurity challenges
Module 7: Advanced Onsite, Masterclass & Simulation
- Participate in a 4-day onsite programme: masterclasses, simulations, study visits, and joint exercises
- Study visit to local partner
- Cross-track hands-on exercise
- Attend mentorship circles and expert-led presentations on diverse AI and cybersecurity topics cross-sectoral cooperation (e.g. data protection, biometrics, AI, etc.)
- Applying the foresight method to Cybersecurity and AI
- Workshop on how to use AI-tools for cyber policy makers
- Mentorship circles
Registration information
Unless specified otherwise, all ITU Academy training courses are open to all interested professionals, irrespective of their race, ethnicity, age, gender, religion, economic status and other diverse backgrounds. We strongly encourage registrations from female participants, and participants from developing countries. This includes least developed countries, small island developing states and landlocked developing countries.
