Unveiling machine learning strategies and considerations in intrusion detection systems: a comprehensive survey
The advancement of communication and internet technology has brought risks to network
security. Thus, Intrusion Detection Systems (IDS) was developed to combat malicious …
security. Thus, Intrusion Detection Systems (IDS) was developed to combat malicious …
[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 …
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 …
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 …
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 …
Enhancing intrusion detection: a hybrid machine and deep learning approach
The volume of data transferred across communication infrastructures has recently increased
due to technological advancements in cloud computing, the Internet of Things (IoT), and …
due to technological advancements in cloud computing, the Internet of Things (IoT), and …
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 …
MuDeLA: multi-level deep learning approach for intrusion detection systems
WL Al-Yaseen, AK Idrees - International Journal of Computers and …, 2023 - Taylor & Francis
In recent years, deep learning techniques have achieved significant results in several fields,
like computer vision, speech recognition, bioinformatics, medical image analysis, and …
like computer vision, speech recognition, bioinformatics, medical image analysis, and …
Intrusion Detection in IoT Systems Using Denoising Autoencoder
Protection against unwanted intrusions is crucial for preserving the integrity and security of
connected devices in the context of Internet of Things (IoT) networks. The growing number of …
connected devices in the context of Internet of Things (IoT) networks. The growing number of …
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 …