To investigate how organizations leverage business analytics to identify, assess, and prioritize cybersecurity risks.
To examine the use of descriptive and diagnostic analytics in monitoring security incidents and vulnerabilities.
To evaluate the effectiveness of analytics-driven risk management frameworks compared to traditional approaches.
To understand the challenges organizations face in integrating analytics into their cybersecurity strategies.
To provide recommendations for improving cybersecurity risk management through enhanced data-driven decision-making practices.
Conduct a comprehensive literature review on cybersecurity risk management and the application of business analytics in this area.
Identify and select organizations (or industry case studies) that represent both traditional and analytics-driven cybersecurity risk management approaches.
Collect qualitative and quantitative data through interviews, surveys, or secondary research focusing on cybersecurity policies, incident reporting, risk assessment procedures, and analytics usage.
Analyze how organizations use key performance indicators (KPIs), dashboards, and reporting tools to track cybersecurity risks and incidents.
Compare and contrast the risk management effectiveness and decision-making quality between traditional and analytics-driven organizations.
Identify success factors, barriers, and challenges to adopting analytics in cybersecurity risk management.
Develop a framework or set of best practices for integrating business analytics into cybersecurity risk management processes.
Prepare a detailed report presenting findings, analysis, and practical recommendations.
Summarize key insights in an executive summary suitable for academic or industry audiences.
Present the findings in a seminar or presentation, demonstrating a clear understanding of business analytics’ impact on cybersecurity risk management.
