[PDF][PDF] Deep learning with dense random neural networks for detecting attacks against IoT-connected home environments
In this paper, we analyze the network attacks that can be launched against IoT gateways,
identify the relevant metrics to detect them, and explain how they can be computed from …
identify the relevant metrics to detect them, and explain how they can be computed from …
An ensemble of deep recurrent neural networks for detecting IoT cyber attacks using network traffic
M Saharkhizan, A Azmoodeh… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Internet-of-Things (IoT) devices and systems will be increasingly targeted by cybercriminals
(including nation state-sponsored or affiliated threat actors) as they become an integral part …
(including nation state-sponsored or affiliated threat actors) as they become an integral part …
Deep-learning based detection for cyber-attacks in IoT networks: A distributed attack detection framework
The widespread use of smart devices and the numerous security weaknesses of networks
has dramatically increased the number of cyber-attacks in the internet of things (IoT) …
has dramatically increased the number of cyber-attacks in the internet of things (IoT) …
[HTML][HTML] DIDS: A Deep Neural Network based real-time Intrusion detection system for IoT
M Vishwakarma, N Kesswani - Decision Analytics Journal, 2022 - Elsevier
The number of people using the Internet of Things (IoT) devices has exploded in recent
years. The instantaneous development in deploying constrained devices in numerous areas …
years. The instantaneous development in deploying constrained devices in numerous areas …
Realguard: A lightweight network intrusion detection system for IoT gateways
Cyber security has become increasingly challenging due to the proliferation of the Internet of
things (IoT), where a massive number of tiny, smart devices push trillion bytes of data to the …
things (IoT), where a massive number of tiny, smart devices push trillion bytes of data to the …
ADEPT: Detection and identification of correlated attack stages in IoT networks
KLK Sudheera, DM Divakaran… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The fast-growing Internet-of-Things (IoT) market has opened up a large threat landscape,
given the wide deployment of IoT devices in both consumer and commercial spaces. Attacks …
given the wide deployment of IoT devices in both consumer and commercial spaces. Attacks …
Towards deep-learning-driven intrusion detection for the internet of things
G Thamilarasu, S Chawla - Sensors, 2019 - mdpi.com
Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices,
applications, and communication networks are becoming increasingly connected and …
applications, and communication networks are becoming increasingly connected and …
Detecting Internet of Things attacks using distributed deep learning
The reliability of Internet of Things (IoT) connected devices is heavily dependent on the
security model employed to protect user data and prevent devices from engaging in …
security model employed to protect user data and prevent devices from engaging in …
Towards learning-automation IoT attack detection through reinforcement learning
As a massive number of the Internet of Things (IoT) devices are deployed, the security and
privacy issues in IoT arouse more and more attention. The IoT attacks are causing …
privacy issues in IoT arouse more and more attention. The IoT attacks are causing …
Lockedge: Low-complexity cyberattack detection in iot edge computing
Internet of Things (IoT) and its applications are becoming commonplace with more devices,
but always at risk of network security. It is therefore crucial for an IoT network design to …
but always at risk of network security. It is therefore crucial for an IoT network design to …