An Investigation into Deep Learning and Machine LearningApproaches for Securing the Internet of Things (IOT)

Abstract

The study explores machine learning and deep learning
(ML) (DL) model helped in solving IoT the computation
problem, which led to the adoption of many domains for its
application in the problem-solving task. Solving a specific
problem, this has led to the idea that deep and machine
learning (DL) (ML) are two powerful approaches to data.
Therefore, the purpose of this article is to provide a
systematic review of “Scanning Machines and Deep
Learning Methods for Internet of Things (IOT) Security and
Privacy” on the current state of research on IoT and its joint
venture with DL. This technique uses discrepancy privacy to
prevent the adversary from understanding the use cases
used to build the target model. The paper concluded that
algorithms deep learning and machine learning were only
developed recently and are not intended for use in
cryptographic applications. However, for researchers who
can implement cryptography, deep learning and machine
learning can be used to implement cryptography