Cybersecurity Strategies for Smart Homes: A Systematic Review of Threats and Mitigation Approaches in IoT Environments

Vera-Mundaca V.G.; Aquino-Trujillo J.Y. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2024) · DOI: 10.18687/leird2024.1.1.307

Resumen

The usage of IoT devices has grown exponentially in smart homes, thanks to the automation benefits they provide. However, this expansion has also increased security vulnerabilities, making these devices attractive targets for cybercriminals. This systematic review analyzes the main cybersecurity threats in domestic IoT environments and the emerging mitigation strategies. Forty-nine studies extracted from the Scopus database were examined, covering articles published between 2020 and April 2024. The results revealed that flooding attacks and authentication and session attacks are the most prevalent. To counter these threats, machine learning and blockchain techniques are highlighted, providing protection against authentication and manipulation. Machine learning methods implemented in intrusion detection systems achieve accuracies ranging from 97.7% to 99.68%. This analysis not only offers a detailed view of current vulnerabilities but also suggests that future research should develop techniques combining machine learning witch blockchain, allowing for greater resilience against diverse attacks.

Instituciones: Universidad Tecnológica del Perú