Machine Learning Benchmarking for Secured IoT Smart Systems

Abstract

Smartness and IoT along with machine learning (ML) lead the research directions nowadays. Smart city, smart campus, smart home, smart vehicle, etc; or if we call it “Smart x” will change how the world entities interact among themselves. This paper provides an ML benchmarking as well as a taxonomy that divides its models into linear and non-linear ones based on the problem type (classification or regression), the targeted security issue, the kind of IoT network, and the used evaluation measure. On the other hand, security algorithms enhanced with ML play a significant role to govern the new era of communication. This paper also provides a case study to apply the ML methods to IoT smart campus (SC) as a model to reach a secured IoT system for data collection and manipulation with guided research directions.