Deep-learning-enabled security issues in the internet of things

Z Lv, L Qiao, J Li, H Song - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
In order to explore the application value of deep learning denoising autoencoder (DAE) in
Internet-of-Things (IoT) fusion security, in this study, a hierarchical intrusion security …

HCRNNIDS: Hybrid convolutional recurrent neural network-based network intrusion detection system

MA Khan - Processes, 2021 - mdpi.com
Nowadays, network attacks are the most crucial problem of modern society. All networks,
from small to large, are vulnerable to network threats. An intrusion detection (ID) system is …

Multi-stage optimized machine learning framework for network intrusion detection

MN Injadat, A Moubayed, AB Nassif… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Cyber-security garnered significant attention due to the increased dependency of individuals
and organizations on the Internet and their concern about the security and privacy of their …

A scalable and hybrid intrusion detection system based on the convolutional-LSTM network

MA Khan, MR Karim, Y Kim - Symmetry, 2019 - mdpi.com
With the rapid advancements of ubiquitous information and communication technologies, a
large number of trustworthy online systems and services have been deployed. However …

Deep learning approach for cyberattack detection

Y Zhou, M Han, L Liu, JS He… - IEEE INFOCOM 2018 …, 2018 - ieeexplore.ieee.org
With the accelerated growth of internet of things IoT application in recent years, cities have
become smarter to optimize resource and improved the quality of life for residents. On the …