- Artificial intelligence
- Cybersecurity
- English
- Kristina Hojstricova
Introductory
- Angola
- Bangladesh
- Benin
- Burkina Faso
- Burundi
- Cambodia
- Central African Republic
- Chad
- Comoros
- Democratic Republic of the Congo
- Djibouti
- Eritrea
- Ethiopia
- Gambia
- Guinea (Republic of)
- Guinea-Bissau
- Haiti
- Kiribati
- Lao People’s Democratic Republic
- Lesotho
- Liberia
- Madagascar
- Malawi
- Mali
- Mauritania
- Mozambique
- Nepal
- Niger
- Rwanda
- São Tomé & Príncipe
- Senegal
- Sierra Leone
- Solomon Islands
- Somalia
- Sudan
- South Sudan
- Timor-Leste
- Togo
- Tuvalu
- Uganda
- Tanzania
- Zambia
Event organizer(s)
Description
In a rapidly evolving digital landscape, the integration of AI and advancements in post-quantum cryptography are reshaping data privacy and security practices worldwide. This comprehensive training course is designed for government officials and regulatory bodies to understand and navigate the complexities introduced by AI-driven data processing and the impending impact of quantum computing on encryption standards.
Through interactive modules, case studies, and practical activities, participants will explore how to implement secure, privacy-centric communication platforms, regulatory frameworks, and risk management strategies that protect sensitive government data, ensure data sovereignty, and future-proof communications against quantum threats.
Members of governments, cybersecurity agencies and regulatory bodies.
Designed for the audience described above, priority will be given to LDCs and SIDS countries engaged in Cyber for Good.
Number of available places for each cohort: 50 accepted participants
Upon completion of this course, participants will be able to:
- Describe the foundations of data privacy in an AI context including essential data privacy concepts, global regulations, and the ethical implications of AI-driven data analytics and profiling in government operations.
- Assess AI-driven data collection risks identifying
- Recognize how AI technology influences data collection, privacy risks, and compliance
- Implement mitigation strategies to safeguard government communications and citizen data.
- Create and refine regulatory frameworks that account for AI-enhanced encryption, real-time threat detection, and the transition to post-quantum cryptography to meet evolving security requirements.
- Apply best practices for secure communication and cyber hygiene that utilize AI for proactive threat monitoring and adopt post-quantum encryption protocols to future-proof government communications.
- Analyze the implications of AI-driven data management and post-quantum cryptography on data residency, jurisdictional compliance, and sovereign cloud solutions for government data storage.
- Build effective risk assessment and compliance monitoring frameworks that ensure data security and jurisdictional adherence using AI-driven tools and post-quantum cryptography
- Identify security vulnerabilities in communication platforms using AI for real-time detection
- Create digital identity verification and post-quantum encryption into e-government services to ensure secure identity protection and access for citizens in a quantum-ready infrastructure.
1. Self-paced content with quiz validation and exercise to practice chapter content
2. Forum to discuss chapter practice exercise
3. One online live session: case study deep dive
4. Digital transformation project assignment
Module quizzes and exercises 25%
Forum 25%
Live session contribution/Active participation 10%
Final assignment 40%
A total score of 70% or higher is required to obtain the ITU certificate
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.