Designing Resilient AI-Based Cybersecurity Frameworks for Small and Medium Enterprises (SMEs)

Femi AG, Osagie AM, Aimefua GIO and Ibrahim U

Published on: 2025-10-11

Abstract

Small and Medium Enterprises (SMEs) face heightened exposure to cyber threats due to limited resources, weak cybersecurity infrastructure, and a lack of specialized expertise. With the rapid pace of digital transformation, SMEs urgently require adaptive and resilient security solutions. This study introduces an AI based cybersecurity framework tailored to SME needs and constraints. The framework leverages machine learning for real time threat detection, predictive analytics to anticipate vulnerabilities, and automated response systems to mitigate risks swiftly. Adopting a mixed methods approach, the research integrates qualitative insights from semi structured interviews with SME stakeholders and quantitative evaluation through prototype deployment in selected environments. Findings show the framework achieves over 96% detection accuracy while significantly reducing incident response times. Ethical and regulatory concerns, including data privacy, transparency, and explainability, addressed through SHAP and LIME models, are incorporated to ensure responsible AI use. Designed for affordability, scalability, and seamless integration with existing SME systems, the framework addresses a major gap in cybersecurity solutions for resource constrained organizations. Beyond contributing to academic literature, it offers SMEs a practical and empirically validated tool to strengthen their cyber resilience. Future research will expand validation on a larger scale, conduct benchmarking, and adapt the system for different regional regulatory contexts.