Deep learning: The frontier for distributed attack detection in fog-to-things computing
A Abeshu, N Chilamkurti - IEEE Communications Magazine, 2018 - ieeexplore.ieee.org
The increase in the number and diversity of smart objects has raised substantial
cybersecurity challenges due to the recent exponential rise in the occurrence and …
cybersecurity challenges due to the recent exponential rise in the occurrence and …
A lightweight model for DDoS attack detection using machine learning techniques
The study in this paper characterizes lightweight IoT networks as being established by
devices with few computer resources, such as reduced battery life, processing power …
devices with few computer resources, such as reduced battery life, processing power …
Timely detection and mitigation of stealthy DDoS attacks via IoT networks
Internet of Things (IoT) networks consist of sensors, actuators, mobile and wearable devices
that can connect to the Internet. With billions of such devices already in the market which …
that can connect to the Internet. With billions of such devices already in the market which …
A framework for malicious traffic detection in IoT healthcare environment
The Internet of things (IoT) has emerged as a topic of intense interest among the research
and industrial community as it has had a revolutionary impact on human life. The rapid …
and industrial community as it has had a revolutionary impact on human life. The rapid …
Anomaly traffic detection in IoT security using graph neural networks
M Gao, L Wu, Q Li, W Chen - Journal of Information Security and …, 2023 - Elsevier
The number of Internet of Things (IoT) devices is expanding quickly as IoT gradually spreads
to all aspects of life. At the same time, IoT devices have emerged as a new attack medium for …
to all aspects of life. At the same time, IoT devices have emerged as a new attack medium for …
A novel deep learning-based intrusion detection system for IOT networks
A Awajan - Computers, 2023 - mdpi.com
The impressive growth rate of the Internet of Things (IoT) has drawn the attention of
cybercriminals more than ever. The growing number of cyber-attacks on IoT devices and …
cybercriminals more than ever. The growing number of cyber-attacks on IoT devices and …
Pulse: an adaptive intrusion detection for the internet of things
The number of diverse interconnected Internet of Things (IoT) devices keeps increasing
exponentially, introducing new security and privacy challenges. These devices tend to …
exponentially, introducing new security and privacy challenges. These devices tend to …
Intrusion Detection Systems for IoT: opportunities and challenges offered by Edge Computing and Machine Learning
P Spadaccino, F Cuomo - arXiv preprint arXiv:2012.01174, 2020 - arxiv.org
Key components of current cybersecurity methods are the Intrusion Detection Systems
(IDSs) were different techniques and architectures are applied to detect intrusions. IDSs can …
(IDSs) were different techniques and architectures are applied to detect intrusions. IDSs can …
Anomaly detection techniques using deep learning in IoT: a survey
IoT technologies is improving life quality by enhancing several real-life smart applications.
IoT includes large number of devices generating huge amount of data which needs large …
IoT includes large number of devices generating huge amount of data which needs large …
Artificial immunity based distributed and fast anomaly detection for Industrial Internet of Things
B Li, Y Chang, H Huang, W Li, T Li, W Chen - Future Generation Computer …, 2023 - Elsevier
Recent years have witnessed an increased attack surface of the Industrial Internet of Things
(IIoT), as the deep convergence of the Internet of Things (IoT) and other information and …
(IIoT), as the deep convergence of the Internet of Things (IoT) and other information and …