Protecting the Internet of Things (IOT) with Machine Learning and Deep Learning Techniques

Abstract

Abstract- Deep learning (DL) and Machine learning (ML) as an IoT paradigm have improved problem-solving, and as a result, their application has expanded to many different fields. This has led to the idea that there are two powerful ways to use data—deep learning (DL) and machine learning (ML)—to solve specific problems. Thus, this article's objective is to provide a thorough analysis of "Scanning Machines and Deep Learning Techniques for Internet of Things (IOT) Security and Privacy," which addresses the current state of IoT research as well as its joint endeavor with DL. This technique stops the adversary from discovering the training data for the target model by utilizing differential privacy. The research's authors concluded that machine learning and deep learning algorithms were developed relatively recently and were never intended for use in cryptography applications. However, researchers with the necessary skills can use deep learning and machine learning to develop cryptography. Index Terms- Internet of Things, Deep Learning, Machine Learning, Security