… Though IoT Security threats can be broadly divided into cyber and physical domains, our
survey is mainly concerned with cyber threats, which can take the form of either active or …

… The denoising autoencoder (DAE) can be constructed by adding noise into the autoencoder.
The noise is added into the training data, and the autoencoder is forced to learn to remove …

… IoT security: Challenges and solution using machine learning, … Lu, “Toward secure and
efficient deep learning inference in … security breach in the Internet of Things,” Internet Things, vol. …

… We discuss the opportunities and challenges involved in applying ML/DL to IoT security.
These opportunities … Learning methods for IoT security have been grouped into ML, DL and RL …

… We used same hyperparameters and regularisation optimisation for bFNN model with the
aim of applying the generalisation of the model to different classification problems. We …

… and assessment of diverse machine learning and deep learning-based network … deep
learning-based solutions used to secure IoT systems. Deep learning can be classified into …

… uses clustering methods. There are some simple rules to implement this method such as i)
Firstly, differentiate the given data set into … In this section, possible research challenges have …

… Numerous organizations and businesses use ML to exploit the … methods of machine learning
that deal with the challenges posed … into this smart era , and then we started using machine …

… security issues in each layer in Section 3. We present various machine and deep learning-based
security … state and issues of IoT security in their survey, which takes into account three …

… , “Toward edgebased deep learning in industrial Internet of Things,” IEEE Internet Things J.,
… -Based channel estimation for Internet of vessels,” IEEE Internet Things J., vol. 7, no. 8, pp. …