Cloud architectures for data security in SMEs: A systematic literature review

Zambrano C.; Enrique L.; Tasayco M.; Daniel J.; Vasquez A.; Felipe S.; Suazo A.; Miguel J. · Proceedings - 2024 14th International Conference on Dependable Systems, Services and Technologies: Trustworthy AI, Internet of Robotics, and Big Data for a Safe and Secure World, DESSERT 2024 (2024) · DOI: 10.1109/dessert65323.2024.11122155

Resumen

Security in the Internet of Things faces unprecedented challenges due to its expanding complexity. Traditional solutions, such as conventional cryptography and centralized security, are no longer sufficient on their own. It is imperative to develop new strategies that incorporate advanced technologies, such as blockchain, software-defined networks, and quantum machine learning. One critical area is the detection of fraudulent URLs, where techniques based on machine and deep learning have shown promising results with traditional models. However, quantum machine learning is presented as an innovative alternative with great potential to significantly improve threat detection. The article concludes by underlining the need to strengthen research and development efforts to create comprehensive and adaptable security solutions for the IoT environment, thus ensuring protection and trust in this interconnected ecosystem. The convergence of these emerging technologies could be key to addressing new security challenges and guaranteeing the integrity and reliability of IoT devices and networks.

Instituciones: Universidad Tecnológica del Perú