The sample data of the existing intrusion detection models of the Internet of Things has
defects such as class imbalance and insufficient feature extraction, which leads to low …

To address the problem of low accuracy of existing network intrusion detection models for
multi-classification of intrusion behaviors and redundancy of data features, a network …

With the advent of the Internet of Things (IoT), the security of the network layer in the IoT is
getting more and more attention. The traditional intrusion detection technologies cannot be …

Abstract Internet of Things (IoT) is a significant area in the digital era for the purpose of data
collection and transferring them on the network without the help of a human, which shows …

The internet of things (IoT) has gained great importance due to its applicability in various
daily life applications and its flexible and scalable framework. The wide and spreading use …

Abstract The Internet of Things (IoT) is vulnerable to network attacks due to the real-time,
open and interactive characteristics, thus causing network security risks. This makes the …

Security is of paramount importance in the number of systems affiliated with increased IoT.
Therefore, in this manuscript, a Stacked Auto Encoder based Deep Neural Network (DNN) …

In view of most existing intrusion detection technologies that cannot meet the actual needs of
the Internet of Things and facing the problems of poor detection effect of complex network …

With the increase in number of IoT devices, the capabilities to provide reliable security and
detect the malicious activities within the IoT network have become quite challenging. We …

The proliferation of Internet of Things (IoTs) technology is being seriously impeded by
insecure networks and data. An effective intrusion detection model is essential for …