Intrusion detection system for large-scale IoT NetFlow networks using machine learning with modified Arithmetic Optimization Algorithm
With the rapid expansion of Internet of Things (IoT) networks, the need for robust security
measures to detect and report potential threats is becoming more urgent. In this paper, we …
measures to detect and report potential threats is becoming more urgent. In this paper, we …
[HTML][HTML] Advancing cybersecurity: a comprehensive review of AI-driven detection techniques
As the number and cleverness of cyber-attacks keep increasing rapidly, it's more important
than ever to have good ways to detect and prevent them. Recognizing cyber threats quickly …
than ever to have good ways to detect and prevent them. Recognizing cyber threats quickly …
[HTML][HTML] Golden jackal optimization algorithm with deep learning assisted intrusion detection system for network security
NO Aljehane, HA Mengash, MM Eltahir… - Alexandria Engineering …, 2024 - Elsevier
Network security is essential to our daily communications and networks. Cybersecurity
researchers initiate the significance of emerging proficient network intrusion detection …
researchers initiate the significance of emerging proficient network intrusion detection …
Passive rule-based approach to detect sinkhole attack in RPL-based internet of things networks
S Al-Sarawi, M Anbar, BA Alabsi, MA Aladaileh… - IEEE …, 2023 - ieeexplore.ieee.org
An Internet of Things (IoT) refers to a network of smart devices that enable data collection
and exchange. RPL is a protocol specifically designed for IPv6 over Low Power Wireless …
and exchange. RPL is a protocol specifically designed for IPv6 over Low Power Wireless …
[HTML][HTML] Attentive transformer deep learning algorithm for intrusion detection on IoT systems using automatic Xplainable feature selection
Recent years have witnessed an in-depth proliferation of the Internet of Things (IoT) and
Industrial Internet of Things (IIoT) systems linked to Industry 4.0 technology. The increasing …
Industrial Internet of Things (IIoT) systems linked to Industry 4.0 technology. The increasing …
Enhanced Intrusion Detection Using Stacked FT-Transformer Architecture.
The function of network intrusion detection systems (NIDS) in protecting networks from
cyberattacks is crucial. Many of the more conventional techniques rely on signature-based …
cyberattacks is crucial. Many of the more conventional techniques rely on signature-based …
[HTML][HTML] AI-driven improvement of monthly average rainfall forecasting in Mecca using grid search optimization for LSTM networks
F Alqahtani - Journal of Water and Climate Change, 2024 - iwaponline.com
Predicting the average monthly rainfall in Mecca is crucial for sustainable development,
resource management, and infrastructure protection in the region. This study aims to …
resource management, and infrastructure protection in the region. This study aims to …
Leveraging metaheuristics for feature selection with machine learning classification for malicious packet detection in computer networks
Robust Intrusion Detection Systems (IDS) are increasingly necessary in the age of big data
due to the growing volume, velocity, and variety of data generated by modern networks …
due to the growing volume, velocity, and variety of data generated by modern networks …
OPSMOTE-ML: an optimized SMOTE with machine learning models for selective forwarding attack detection in low power and lossy networks of internet of things
Abstract The Internet of Things represents a rapidly evolving networking paradigm that
brings numerous benefits through its diverse applications. Advances in embedded system …
brings numerous benefits through its diverse applications. Advances in embedded system …
Optimizing long short-term memory networks for univariate time series forecasting: a comprehensive guide
M Abotaleb, PK Dutta - Hybrid Information Systems: Non-Linear …, 2024 - degruyter.com
This article presents a comprehensive exploration of the adaptation of long short-term
memory (LSTM) neural networks for univariate time series forecasting, a critical area in …
memory (LSTM) neural networks for univariate time series forecasting, a critical area in …