Composition of hybrid deep learning model and feature optimization for intrusion detection system

A Henry, S Gautam, S Khanna, K Rabie, T Shongwe… - Sensors, 2023 - mdpi.com
Recently, with the massive growth of IoT devices, the attack surfaces have also intensified.
Thus, cybersecurity has become a critical component to protect organizational boundaries …

Application of artificial intelligence to network forensics: Survey, challenges and future directions

S Rizvi, M Scanlon, J Mcgibney, J Sheppard - Ieee Access, 2022 - ieeexplore.ieee.org
Network forensics focuses on the identification and investigation of internal and external
network attacks, the reverse engineering of network protocols, and the uninstrumented …

[PDF][PDF] Network intrusion detection systems: A systematic literature review of hybrid deep learning approaches

SK Wanjau, GM Wambugu, AM Oirere - 2022 - repository.mut.ac.ke
Network Intrusion Detection Systems (NIDSs) have become standard security solutions that
endeavours to discover unauthorized access to an organizational computer network by …

Sine-Cosine-Adopted African Vultures Optimization with Ensemble Autoencoder-Based Intrusion Detection for Cybersecurity in CPS Environment

L Almuqren, F Al-Mutiri, M Maashi, H Mohsen, AM Hilal… - Sensors, 2023 - mdpi.com
A Cyber-Physical System (CPS) is a network of cyber and physical elements that interact
with each other. In recent years, there has been a drastic increase in the utilization of CPSs …

Majority voting and feature selection based network intrusion detection system

DR Patil, TM Pattewar - EAI Endorsed Transactions on Scalable Information …, 2022 - eudl.eu
Attackers continually foster new endeavours and attack strategies meant to keep away from
safeguards. Many attacks have an effect on other malware or social engineering to collect …

Incremental Update Intrusion Detection for Industry 5.0 Security: A Graph Attention Network-Enabled Approach

Y Wu, L Nie, X Xiong, B Sadoun… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The Industry 5.0 (I5) incorporates numerous emerging technologies that enable the
perception, management, interaction, and control of real physical objects. As cyber attacks …

Detecting Network Intrusion in Cloud Environment Through Ensemble Learning and Feature Selection Approach

M Khan, M Haroon - SN Computer Science, 2023 - Springer
The use of the Internet is enhanced drastically in the current era, which connects multiple
computers in a network and a group of devices. In addition, every sector uses the Internet to …

Network Intrusion Detection and Dynamic Defense Method Based on Unsupervised Machine Learning

Q Wang, M Xie, Z Wu, D Yang - 2023 International Conference …, 2023 - ieeexplore.ieee.org
With the rapid development of the Internet, network security issues have become
increasingly prominent, and the traditional rule-based and signature-based intrusion …

Reinforcement Learning Meets Network Intrusion Detection: A Transferable and Adaptable Framework for Anomaly Behavior Identification

M He, X Wang, P Wei, L Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Anomaly detection plays an essential role in network security and traffic classification. Many
studies have focused on anomaly detection to improve network security, including machine …

Intrusion Detection Using Attention-Based CNN-LSTM Model

B Al-Omar, Z Trabelsi - IFIP International Conference on Artificial …, 2023 - Springer
With the rise of sophisticated cyberattacks and the advent of complex and diverse
technological systems, traditional methods of intrusion detection have become insufficient …