A review of plant phenotypic image recognition technology based on deep learning
Plant phenotypic image recognition (PPIR) is an important branch of smart agriculture. In
recent years, deep learning has achieved significant breakthroughs in image recognition …
recent years, deep learning has achieved significant breakthroughs in image recognition …
Towards secure intrusion detection systems using deep learning techniques: Comprehensive analysis and review
Providing a high-performance Intrusion Detection System (IDS) can be very effective in
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
controlling malicious behaviors and cyber-attacks. Regarding the ever-growing negative …
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 …
from small to large, are vulnerable to network threats. An intrusion detection (ID) system is …
IoTBoT-IDS: A novel statistical learning-enabled botnet detection framework for protecting networks of smart cities
J Ashraf, M Keshk, N Moustafa, M Abdel-Basset… - Sustainable Cities and …, 2021 - Elsevier
The rapid proliferation of the Internet of Things (IoT) systems, has enabled transforming
urban areas into smart cities. Smart cities' paradigm has resulted in improved quality of life …
urban areas into smart cities. Smart cities' paradigm has resulted in improved quality of life …
On the performance of machine learning models for anomaly-based intelligent intrusion detection systems for the internet of things
G Abdelmoumin, DB Rawat… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Anomaly-based machine learning-enabled intrusion detection systems (AML-IDSs) show
low performance and prediction accuracy while detecting intrusions in the Internet of Things …
low performance and prediction accuracy while detecting intrusions in the Internet of Things …
Security analysis of DDoS attacks using machine learning algorithms in networks traffic
RJ Alzahrani, A Alzahrani - Electronics, 2021 - mdpi.com
The recent advance in information technology has created a new era named the Internet of
Things (IoT). This new technology allows objects (things) to be connected to the Internet …
Things (IoT). This new technology allows objects (things) to be connected to the Internet …
A taxonomy of machine-learning-based intrusion detection systems for the internet of things: A survey
A Jamalipour, S Murali - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
The Internet of Things (IoT) is an emerging technology that has earned a lot of research
attention and technical revolution in recent years. Significantly, IoT connects and integrates …
attention and technical revolution in recent years. Significantly, IoT connects and integrates …
A multi-stage classification approach for iot intrusion detection based on clustering with oversampling
Intrusion detection of IoT-based data is a hot topic and has received a lot of interests from
researchers and practitioners since the security of IoT networks is crucial. Both supervised …
researchers and practitioners since the security of IoT networks is crucial. Both supervised …
Man-in-the-Middle attack mitigation in internet of medical things
The Internet of Medical Things are susceptible to Man-in-the-Middle (MitM) attack, which can
identify healthcare emergency of monitored patients and replay normal physiological data to …
identify healthcare emergency of monitored patients and replay normal physiological data to …
An anomaly-based intrusion detection system for internet of medical things networks
Over the past few years, the healthcare sector is being transformed due to the rise of the
Internet of Things (IoT) and the introduction of the Internet of Medical Things (IoMT) …
Internet of Things (IoT) and the introduction of the Internet of Medical Things (IoMT) …