A Smart Security Framework for IoT Devices
Sonal Sune, Jigang Liu · 2022
While the rapid development of the IoT technology and application has played a critical role in the latest economic growth, the potential issues in security and privacy caused by IoT devices have brought extensive attention from both academia and industry recently. Although cryptography algorithms have been widely used in solving security and privacy problems for years, it is extremely challenging in applying them to IoT devices due to the limited resources available on those tiny devices. In this research paper, a new framework was proposed in assisting manufacture industries as well as IoT application developers in evaluating and selecting proper crypto algorithms and implementations for their IoT products. By combining the comparative textual analysis method and the decision tree algorithm, the new framework is well supported by the supervised machine learning approach. As a proof of the concept, selected case studies were carefully designed and performed based on the available data. With a systematic review and analysis of the current development in the field, the results produced by those case studies have exhibited the promising potential as well as the unique features presented in this newly proposed framework.