Addressing Imbalanced Data in Network Intrusion Detection: A Review and Survey.

EA Al-Qarni, GA Al-Asmari - International Journal of …, 2024 - search.ebscohost.com
The proliferation of internet-connected devices, including smartphones, smartwatches, and
computers, has led to an unprecedented surge in data generation. The rapid rise in device …

Enhancing Prediction Models' Performance for Breast Cancer using SMOTE Technique

A Alsabry, M Algabri, AM Ahsan… - … on Emerging Smart …, 2023 - ieeexplore.ieee.org
Breast cancer (BC) is a critical public health concern, and the development of accurate
prediction models is crucial for early detection. However, predicting BC using imbalanced …

Reinforcing Network Security: Network Attack Detection Using Random Grove Blend in Weighted MLP Layers

A Binbusayyis - Mathematics, 2024 - mdpi.com
In the modern world, the evolution of the internet supports the automation of several tasks,
such as communication, education, sports, etc. Conversely, it is prone to several types of …

[PDF][PDF] Ensemble Voting-Based Anomaly Detection for a Smart Grid Communication Infrastructure.

H Alshede, L Nassef, N Alowidi… - Intelligent Automation & …, 2023 - cdn.techscience.cn
Advanced Metering Infrastructure (AMI) is the metering network of the smart grid that
enables bidirectional communications between each consumer's premises and the …

Breast Cancer Prediction Framework Based on Iterative Optimization with Bayesian Hyperparameter Tuning

A Alsabry, M Algabri, AM Ahsan… - … on Emerging Smart …, 2023 - ieeexplore.ieee.org
Breast cancer (BC) is a major health concern affecting women worldwide, and early
detection is crucial for effective treatment and improved survival rates. In this study, we …

Unsupervised Graph Structure Learning Based on Optimal Graph Topology Modeling and Adaptive Data Augmentation

D An, Z Pan, Q Zhao, W Liu, J Liu - Mathematics, 2024 - mdpi.com
Graph neural networks (GNNs) are effective for structured data analysis but face reduced
learning accuracy due to noisy connections and the necessity for explicit graph structures …

A Hybrid Meta-heuristics Algorithm: XGBoost-Based Approach for IDS in IoT

S Bajpai, K Sharma, BK Chaurasia - SN Computer Science, 2024 - Springer
In recent years, the importance of the Internet of Things (IoT) and its applications has
increased. IoT networks are diverse, allowing for various real-time applications and making …

[PDF][PDF] One Dimensional Conv-BiLSTMNetwork with AttentionMechanism for IoT Intrusion Detection.

B Omarov, Z Sailaukyzy, A Bigaliyeva… - … Materials & Continua, 2023 - cdn.techscience.cn
In the face of escalating intricacy and heterogeneity within Internet of Things (IoT) network
landscapes, the imperative for adept intrusion detection techniques has never been more …

Deep learning model for intrusion detection system utilizing convolution neural network

WF Kamil, IJ Mohammed - Open Engineering, 2023 - degruyter.com
An integral part of any reliable network security infrastructure is the intrusion detection
system (IDS). Early attack detection can stop adversaries from further intruding on a network …

Intelligent Computing Techniques for Sustainable Cybersecurity: Enhancing Threat Detection and Response

ASR Praneeth, G Shyashyankhareddy… - … Conference on Intelligent …, 2023 - Springer
Cyberthreats including hacking, data breaches, and malware assaults have significantly
increased as a result of digitalization and the Internet of Things'(IoT) extensive use. As a …