Edge computing with artificial intelligence: A machine learning perspective

H Hua, Y Li, T Wang, N Dong, W Li, J Cao - ACM Computing Surveys, 2023 - dl.acm.org
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 …

Edge computing in industrial internet of things: Architecture, advances and challenges

T Qiu, J Chi, X Zhou, Z Ning… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
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 …

[HTML][HTML] IoT in smart cities: A survey of technologies, practices and challenges

AS Syed, D Sierra-Sosa, A Kumar, A Elmaghraby - Smart Cities, 2021 - mdpi.com
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 …

Design and development of a deep learning-based model for anomaly detection in IoT networks

I Ullah, QH Mahmoud - IEEE Access, 2021 - ieeexplore.ieee.org
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 …

Deep learning methods in network intrusion detection: A survey and an objective comparison

S Gamage, J Samarabandu - Journal of Network and Computer …, 2020 - Elsevier
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 …

[HTML][HTML] 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 …

Design and development of RNN anomaly detection model for IoT networks

I Ullah, QH Mahmoud - IEEE Access, 2022 - ieeexplore.ieee.org
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 …

A survey on deep learning for cybersecurity: Progress, challenges, and opportunities

M Macas, C Wu, W Fuertes - Computer Networks, 2022 - Elsevier
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 …

[HTML][HTML] A survey of deep learning methods for cyber security

DS Berman, AL Buczak, JS Chavis, CL Corbett - Information, 2019 - mdpi.com
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 …

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 …