[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 …
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 …
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 …
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 …
An LSTM‐based novel near‐real‐time multiclass network intrusion detection system for complex cloud environments
The Internet is connected with everyone for sharing and monitoring digital information.
However, securing network resources from malicious activities is critical for several …
However, securing network resources from malicious activities is critical for several …
Intrusion Detection With Deep Learning Classifiers: A Synergistic Approach of Probabilistic Clustering and Human Expertise to Reduce False Alarms
Intrusion detection systems (IDS) have seen an increasing number of proposals by
researchers utilizing deep learning (DL) to safeguard critical networks. However, they often …
researchers utilizing deep learning (DL) to safeguard critical networks. However, they often …