A Systematic Review of Security Vulnerabilities in Smart Home Devices and Mitigation Techniques

TL;DR

This paper systematically reviews security vulnerabilities in smart home IoT devices, analyzing threats and mitigation techniques, and highlights the effectiveness and challenges of advanced cryptographic and AI-based security strategies.

Contribution

It categorizes vulnerabilities and evaluates mitigation techniques, emphasizing the need for scalable, efficient, and adaptive security solutions for smart home environments.

Findings

AI-driven anomaly detection enhances security

Post-quantum encryption improves resilience but is resource-intensive

Blockchain and zero-trust models increase security resilience

Abstract

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.