Internet of Things (IoT) is a network of several hardware and software systems which is broadly based upon internet services and several state-of-the-art sensing and communication technologies. The emergence of 5G technology will witness a further surge in the growth of IoT across the world but simultaneously security concerns pertinent to the IoT technology also need rigorous evaluations. This article will present a thorough survey of the security challenges in an IoT network, recent cases of attacks on IoT technology, communication protocols prevalent in IoT systems and the role of artificial intelligence (AI) in IoT security. For the first time, all the major attributes related to IoT security along with potential solutions using AI are reviewed and articulated together. This work would act as a useful resource for understanding useful perspectives in future research focused around the development of more secured IoT communication protocols as well as AI tools for handling privacy and security in IoT.

No abstract

of machine learning of equivariant properties, machine learning-aided statistical mechanics, the incorporation of ab initio approaches in multiscale models of materials processing and application of machine learning in uncertainty quantification. In addition to the above, the applicability of Bayesian approach for multiscale modelling will be discussed. Critical issues related to the multiscale materials modelling are also discussed.This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan (http://energy.gov/downloads/doe-publicaccess-plan).

No abstract