Economic development and the comfort-loving nature of human beings in recent years have resulted in increased energy demand. Since energy resources are scarce and should be …
Anomaly detection has been used for decades to identify and extract anomalous components from data. Many techniques have been used to detect anomalies. One of the …
In this paper, we present a survey of deep learning approaches for cyber security intrusion detection, the datasets used, and a comparative study. Specifically, we provide a review of …
The use of deep learning models for the network intrusion detection task has been an active area of research in cybersecurity. Although several excellent surveys cover the growing …
In the past several years, the world has witnessed an acute surge in the production and usage of smart devices which are referred to as the Internet of Things (IoT). These devices …
A Thakkar, R Lohiya - Archives of Computational Methods in Engineering, 2021 - Springer
Abstract Internet of Things (IoT) is widely accepted technology in both industrial as well as academic field. The objective of IoT is to combine the physical environment with the cyber …
A Aldweesh, A Derhab, AZ Emam - Knowledge-Based Systems, 2020 - Elsevier
The massive growth of data that are transmitted through a variety of devices and communication protocols have raised serious security concerns, which have increased the …
The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in …
Anomaly detection is concerned with identifying data patterns that deviate remarkably from the expected behavior. This is an important research problem, due to its broad set of …