Cybersecurity Integrated with AI

Program Description

Cybersecurity in Ghana’s banking sector is evolving rapidly, driven by AI-powered threat detection, anomaly monitoring, and compliance automation. As banks adopt AI tools to secure digital assets, they face new risks: algorithmic bias, explainability gaps, and cyber vulnerabilities in AI models themselves.

This course equips professionals to integrate AI responsibly into cybersecurity strategies, aligning with Bank of Ghana directives, ISO/IEC 27001, and biblical principles of vigilance, stewardship, and accountability.

 LEARNING OBJECTIVES

·         Explain how AI enhances and complicates cybersecurity in banking.

·         Identify AI-specific cyber risks (e.g. adversarial attacks, model poisoning)

·         Apply ISO/IEC 27001 controls to AI-integrated systems

·         Use AI tools for threat detection, incident response, and compliance

·         Evaluate ethical implications of AI in cybersecurity.

·         Analyze Ghanaian case studies of AI-enabled cyber defense

 PRE-REQUISITE

·         Basic understanding of cybersecurity principles

·         Familiarity with AI concepts (machine learning, NLP, predictive analytics)

·         Awareness of Ghanaian banking regulations and ISO standards

 COURSE CONTENTS

Module 1: Cybersecurity Fundamentals in Banking

·         Threat landscape in Ghana’s digital banking

·         Core principles: confidentiality, integrity, availability

Module 2: AI in Cybersecurity

·         AI for threat detection, anomaly monitoring, phishing prevention

·         Risks: adversarial inputs, explainability, data leakage

Module 3: Governance & ISO Alignment

·         ISO/IEC 27001:2013 controls for AI systems

·         Mapping AI risks to Bank of Ghana cybersecurity directives

·         Faith-based lens: vigilance, stewardship, accountability

Module 4: AI Tools & Techniques

·         Machine learning for fraud detection

·         NLP for phishing email classification

·         Predictive analytics for breach forecasting

Module 5: Case Studies & Group Work

·         Case 1: AI detecting SIM swap fraud in Ghana

·         Case 2: Adversarial attack on chatbot interface

·         Case 3: Ethical dilemma—AI flagging low-income users as high-risk

Module 6: Future Trends & Reflection

·         AI-driven zero-trust architectures

·         Cyber resilience in AI-enabled banking

Cybersecurity Integrated with AI

Duration: 4 days

Skill Level: Foundation

Delivery Mode: In-person

Month: September