Edge computing with artificial intelligence: A machine learning perspective
Recent years have witnessed the widespread popularity of Internet of things (IoT). By
providing sufficient data for model training and inference, IoT has promoted the development …
providing sufficient data for model training and inference, IoT has promoted the development …
Edge computing in industrial internet of things: Architecture, advances and challenges
The Industrial Internet of Things (IIoT) is a crucial research field spawned by the Internet of
Things (IoT). IIoT links all types of industrial equipment through the network; establishes data …
Things (IoT). IIoT links all types of industrial equipment through the network; establishes data …
IoT in smart cities: A survey of technologies, practices and challenges
Internet of Things (IoT) is a system that integrates different devices and technologies,
removing the necessity of human intervention. This enables the capacity of having smart (or …
removing the necessity of human intervention. This enables the capacity of having smart (or …
Design and development of a deep learning-based model for anomaly detection in IoT networks
The growing development of IoT (Internet of Things) devices creates a large attack surface
for cybercriminals to conduct potentially more destructive cyberattacks; as a result, the …
for cybercriminals to conduct potentially more destructive cyberattacks; as a result, the …
Machine learning and deep learning methods for intrusion detection systems: A survey
H Liu, B Lang - applied sciences, 2019 - mdpi.com
Networks play important roles in modern life, and cyber security has become a vital research
area. An intrusion detection system (IDS) which is an important cyber security technique …
area. An intrusion detection system (IDS) which is an important cyber security technique …
Deep learning methods in network intrusion detection: A survey and an objective comparison
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 …
area of research in cybersecurity. Although several excellent surveys cover the growing …
A survey of deep learning methods for cyber security
This survey paper describes a literature review of deep learning (DL) methods for cyber
security applications. A short tutorial-style description of each DL method is provided …
security applications. A short tutorial-style description of each DL method is provided …
Design and development of RNN anomaly detection model for IoT networks
Cybersecurity is important today because of the increasing growth of the Internet of Things
(IoT), which has resulted in a variety of attacks on computer systems and networks. Cyber …
(IoT), which has resulted in a variety of attacks on computer systems and networks. Cyber …
A survey on deep learning for cybersecurity: Progress, challenges, and opportunities
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
Hybrid intrusion detection using mapreduce based black widow optimized convolutional long short-term memory neural networks
PR Kanna, P Santhi - Expert Systems with Applications, 2022 - Elsevier
The recent advancements in information and communication technologies have led to an
increasing number of online systems and services. These online systems can utilize …
increasing number of online systems and services. These online systems can utilize …