Explainable AI for Transparent Cyber-Risk Assessment and Decision-Making
Chhavi Mohitkar, D. Lakshmi · Advances in computational intelligence and robotics book series · 2024
The research paper “Explainable AI for Transparent Cyber-Risk Assessment and Decision-Making” explores the integration of explainable artificial intelligence (XAI) in enhancing the transparency and effectiveness of cyber-risk assessments. It highlights the necessity for AI systems to provide interpretable outputs, enabling stakeholders to understand the rationale behind risk evaluations and decisions. The study emphasizes that traditional models often lack transparency, leading to challenges in trust and accountability in cybersecurity contexts. By employing XAI techniques, the paper demonstrates improved decision-making processes, allowing organizations to better manage cyber threats and vulnerabilities. Furthermore, it addresses the limitations of existing frameworks, advocating for a more robust approach that combines technical rigor with user-centric design. Ultimately, the findings suggest that XAI not only enhances risk assessment accuracy but also fosters a culture of informed decision-making in cybersecurity.