[HTML][HTML] Dependable intrusion detection system using deep convolutional neural network: A novel framework and performance evaluation approach
Intrusion detection systems (IDS) play a critical role in safeguarding computer networks
against unauthorized access and malicious activities. However, traditional IDS approaches …
against unauthorized access and malicious activities. However, traditional IDS approaches …
APT adversarial defence mechanism for industrial IoT enabled cyber-physical system
The objective of Advanced Persistent Threat (APT) attacks is to exploit Cyber-Physical
Systems (CPSs) in combination with the Industrial Internet of Things (I-IoT) by using fast …
Systems (CPSs) in combination with the Industrial Internet of Things (I-IoT) by using fast …
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 …
A Comprehensive Survey of Masked Faces: Recognition, Detection, and Unmasking
Masked face recognition (MFR) has emerged as a critical domain in biometric identification,
especially by the global COVID-19 pandemic, which introduced widespread face masks …
especially by the global COVID-19 pandemic, which introduced widespread face masks …
DDoS attack detection and mitigation using deep neural network in SDN environment
In the contemporary digital landscape, the escalating threat landscape of cyber attacks,
particularly distributed denial-of-service (DDoS) attacks, has become a paramount concern …
particularly distributed denial-of-service (DDoS) attacks, has become a paramount concern …
An efficient deep learning mechanisms for IoT/Non-IoT devices classification and attack detection in SDN-enabled smart environment
P Malini, KR Kavitha - Computers & Security, 2024 - Elsevier
In recent years, the development of Internet of Things (IoT) applications has increased,
resulting in higher demands for sufficient bandwidth, data rates, latency, and quality of …
resulting in higher demands for sufficient bandwidth, data rates, latency, and quality of …
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 …
Network Intrusion Detection using Deep Convolution Neural Network
In recent years, with the rise of cyber attacks, intrusion detection systems (IDS) have become
an essential component of network security. Deep learning-based approaches have shown …
an essential component of network security. Deep learning-based approaches have shown …
A Survey of Deep Learning Technologies for Intrusion Detection in Internet of Things
The Internet of Things (IoT) is transforming how we live and work, and its applications are
widespread, spanning smart homes, industrial monitoring, smart cities, healthcare …
widespread, spanning smart homes, industrial monitoring, smart cities, healthcare …
A multi-label network attack detection approach based on two-stage model fusion
Y Huang, J Gou, Z Fan, Y Liao, Y Zhuang - Journal of Information Security …, 2024 - Elsevier
The diversification and complexity of network attacks pose a serious challenge to network
security and lead to the phenomenon of overlapping attributes of network attack behaviors …
security and lead to the phenomenon of overlapping attributes of network attack behaviors …