A deep learning-based intrusion detection system for MQTT enabled IoT
A large number of smart devices in Internet of Things (IoT) environments communicate via
different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely …
different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely …
[HTML][HTML] Deep learning for cyber threat detection in IoT networks: A review
A Aldhaheri, F Alwahedi, MA Ferrag, A Battah - Internet of Things and Cyber …, 2023 - Elsevier
Abstract The Internet of Things (IoT) has revolutionized modern tech with interconnected
smart devices. While these innovations offer unprecedented opportunities, they also …
smart devices. While these innovations offer unprecedented opportunities, they also …
Machine learning and the Internet of Things security: Solutions and open challenges
Abstract Internet of Things (IoT) is a pervasively-used technology for the last few years. IoT
technologies are also responsible for intensifying various everyday smart applications …
technologies are also responsible for intensifying various everyday smart applications …
Anomaly-based intrusion detection system in the Internet of Things using a convolutional neural network and multi-objective enhanced Capuchin Search Algorithm
H Asgharzadeh, A Ghaffari, M Masdari… - Journal of Parallel and …, 2023 - Elsevier
Nowadays, the growth and pervasiveness of Internet of Things (IoT) devices have led to
increased attacks by hackers and attackers. On the other hand, using IoT infrastructure in …
increased attacks by hackers and attackers. On the other hand, using IoT infrastructure in …
Deep learning enabled intrusion detection system for Industrial IOT environment
H Nandanwar, R Katarya - Expert Systems with Applications, 2024 - Elsevier
The prevalence of security vulnerabilities in Internet of Things (IoT) applications poses a
serious threat to enterprise systems, necessitating sophisticated and reliable defense …
serious threat to enterprise systems, necessitating sophisticated and reliable defense …
Application of artificial intelligence to network forensics: Survey, challenges and future directions
Network forensics focuses on the identification and investigation of internal and external
network attacks, the reverse engineering of network protocols, and the uninstrumented …
network attacks, the reverse engineering of network protocols, and the uninstrumented …
An improved long short term memory network for intrusion detection
Over the years, intrusion detection system has played a crucial role in network security by
discovering attacks from network traffics and generating an alarm signal to be sent to the …
discovering attacks from network traffics and generating an alarm signal to be sent to the …
Security in internet of things: a review on approaches based on blockchain, machine learning, cryptography, and quantum computing
Abstract The Internet of Things (IoT) is an important virtual network that allows remote users
to access linked multimedia devices. The development of IoT and its ubiquitous application …
to access linked multimedia devices. The development of IoT and its ubiquitous application …
Optimized deep autoencoder model for internet of things intruder detection
B Lahasan, H Samma - IEEE Access, 2022 - ieeexplore.ieee.org
The development of an optimized deep learning intruder detection model that could be
executed on IoT devices with limited hardware support has several advantages, such as the …
executed on IoT devices with limited hardware support has several advantages, such as the …
Secure and efficient coded multi-access edge computing with generalized graph neural networks
A Asheralieva, D Niyato - IEEE Transactions on Mobile …, 2022 - ieeexplore.ieee.org
We formulate a novel framework to improve security and utility of the coded multi-access
edge computing (MEC) network for Internet of Things (IoT) applications where multiple edge …
edge computing (MEC) network for Internet of Things (IoT) applications where multiple edge …