A Systematic Review of Security Vulnerabilities in Smart Home Devices and Mitigation Techniques
This incremental review addresses cybersecurity risks for smart home users and developers, highlighting gaps in existing solutions.
The study tackled security vulnerabilities in smart home IoT devices by categorizing threats and evaluating mitigation techniques like post-quantum encryption and AI-driven anomaly detection, finding them effective but with challenges in computational demands and scalability.
Smart homes that integrate Internet of Things (IoT) devices face increasing cybersecurity risks, posing significant challenges to these environments. The study explores security threats in smart homes ecosystems, categorizing them into vulnerabilities at the network layer, device level, and those from cloud-based and AI-driven systems. Research findings indicate that post-quantum encryption, coupled with AI-driven anomaly detection, is highly effective in enhancing security; however, computational resource demands present significant challenges. Blockchain authentication together with zero-trust structures builds security resilience, although they need changes to existing infrastructure. The specific security strategies show their effectiveness through ANOVA, Chi-square tests, and Monte Carlo simulations yet lack sufficient scalability according to the results. The research demonstrates the requirement for improvement in cryptographic techniques, alongside AI-enhanced threat detection and adaptive security models which must achieve a balance between performance and efficiency and real-time applicability within smart home ecosystems.