Big data analytics and e-governance: Actors, opportunities, tensions, and applications
We present a systematic review of peer-reviewed articles, empirical as well as conceptual,
investigating the integration of big data analytics in e-governance within business …
investigating the integration of big data analytics in e-governance within business …
Security in internet of things: a review on approaches based on blockchain, machine learning, cryptography, and quantum computing
Abstract The Internet of Things (IoT) is an important virtual network that allows remote users
to access linked multimedia devices. The development of IoT and its ubiquitous application …
to access linked multimedia devices. The development of IoT and its ubiquitous application …
CNN-CNN: Dual Convolutional Neural Network Approach for Feature Selection and Attack Detection on Internet of Things Networks
The Internet of Things (IoT) has brought significant advancements that have connected our
world more closely than ever before. However, the growing number of connected devices …
world more closely than ever before. However, the growing number of connected devices …
Micro-directional propagation method based on user clustering
With the development of recommendation technology, it is of great significance to analyze
users' digital footprints on social networking sites, extract user behavior rules, and make a …
users' digital footprints on social networking sites, extract user behavior rules, and make a …
[HTML][HTML] Enhancing IoT network security through deep learning-powered Intrusion Detection System
The rapid growth of the Internet of Things (IoT) has brought about a global concern for the
security of interconnected devices and networks. This necessitates the use of efficient …
security of interconnected devices and networks. This necessitates the use of efficient …
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 …
An ensemble deep learning based IDS for IoT using Lambda architecture
R Alghamdi, M Bellaiche - Cybersecurity, 2023 - Springer
Abstract The Internet of Things (IoT) has revolutionized our world today by providing greater
levels of accessibility, connectivity and ease to our everyday lives. It enables massive …
levels of accessibility, connectivity and ease to our everyday lives. It enables massive …
Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction
Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS)
play a critical role in protecting interconnected networks by detecting malicious actors and …
play a critical role in protecting interconnected networks by detecting malicious actors and …
Crsf: An intrusion detection framework for industrial internet of things based on pretrained cnn2d-rnn and svm
S Li, G Chai, Y Wang, G Zhou, Z Li, D Yu, R Gao - IEEE Access, 2023 - ieeexplore.ieee.org
The traditional support vector machine (SVM) requires manual feature extraction to improve
classification performance and relies on the expressive power of manually extracted …
classification performance and relies on the expressive power of manually extracted …
XAI-IDS: Toward Proposing an Explainable Artificial Intelligence Framework for Enhancing Network Intrusion Detection Systems
O Arreche, T Guntur, M Abdallah - Applied Sciences, 2024 - mdpi.com
The exponential growth of network intrusions necessitates the development of advanced
artificial intelligence (AI) techniques for intrusion detection systems (IDSs). However, the …
artificial intelligence (AI) techniques for intrusion detection systems (IDSs). However, the …