RAIDS: robust autoencoder-based intrusion detection system model against adversarial attacks
Abstract Machine learning-based intrusion detection systems (IDS) are essential security
functions in conventional and software-defined networks alike. Their success and the …
functions in conventional and software-defined networks alike. Their success and the …
Malware detection in internet of things (IoT) devices using deep learning
Internet of Things (IoT) devices usage is increasing exponentially with the spread of the
internet. With the increasing capacity of data on IoT devices, these devices are becoming …
internet. With the increasing capacity of data on IoT devices, these devices are becoming …
Machine learning-based adaptive synthetic sampling technique for intrusion detection
Traditional firewalls and data encryption techniques can no longer match the demands of
current IoT network security due to the rising amount and variety of network threats. In order …
current IoT network security due to the rising amount and variety of network threats. In order …
Exploring lightweight deep learning solution for malware detection in IoT constraint environment
The present era is facing the industrial revolution. Machine-to-Machine (M2M)
communication paradigm is becoming prevalent. Resultantly, the computational capabilities …
communication paradigm is becoming prevalent. Resultantly, the computational capabilities …
Anomaly detection using deep convolutional generative adversarial networks in the internet of things
AK Mishra, S Paliwal, G Srivastava - ISA transactions, 2024 - Elsevier
Advanced 5 G and 6 G technologies have accelerated the adoption of the Internet of Things
(IoT) and are a priority in providing support for high-speed communication and fast data …
(IoT) and are a priority in providing support for high-speed communication and fast data …
Brain–Computer Interface: The HOL–SSA Decomposition and Two-Phase Classification on the HGD EEG Data
MJ Antony, BP Sankaralingam, S Khan, A Almjally… - Diagnostics, 2023 - mdpi.com
An efficient processing approach is essential for increasing identification accuracy since the
electroencephalogram (EEG) signals produced by the Brain–Computer Interface (BCI) …
electroencephalogram (EEG) signals produced by the Brain–Computer Interface (BCI) …
Intrusion detection in smart IoT devices for people with disabilities
An intrusion Detection System (IDS) is a system that resides inside the network and monitors
all incoming and outgoing traffic. It prevents unethical activities from happening over the …
all incoming and outgoing traffic. It prevents unethical activities from happening over the …
Improving Performance of Intrusion Detection Using ALO Selected Features and GRU Network
K Sundaram, S Subramanian, Y Natarajan… - SN Computer …, 2023 - Springer
The expansion of the internet has not only opened up new possibilities for cooperation,
networking, and ingenuity, but also presented fresh security hazards and complexities. As …
networking, and ingenuity, but also presented fresh security hazards and complexities. As …
Application of Deep Neural Network with Frequency Domain Filtering in the Field of Intrusion Detection
Z Wang, J Li, Z Xu, S Yang, D He… - International Journal of …, 2023 - Wiley Online Library
In the field of intrusion detection, existing deep learning algorithms have limited capability to
effectively represent network data features, making it challenging to model the complex …
effectively represent network data features, making it challenging to model the complex …
Swarm Optimized Differential Evolution and Probabilistic Extreme Learning based Intrusion Detection in MANET
R Sathiya, N Yuvaraj - Computers & Security, 2024 - Elsevier
MANETs are an attracting mechanism foSr several applications, to name a few being rescue
functioning, environmental surveillance and so on due to the reason that they allow users to …
functioning, environmental surveillance and so on due to the reason that they allow users to …