Early Detection of Unknown Attacks with Algorithms for Structured Data

T Puccetti - 2023 IEEE 34th International Symposium on …, 2023 - ieeexplore.ieee.org
The increasing reliance on modern information and communication technology (ICT)
systems exposes organizations to a wide range of cybersecurity threats. In this context …

Facilitating DoS Attack Detection using Unsupervised Anomaly Detection

C Bellas, G Kougka, A Naskos, A Gounaris… - Proceedings of the 34th …, 2022 - dl.acm.org
Modern techniques in intrusion and DoS (Denial of Service) detection tend to be either
supervised or semi-supervised, ie, they require training and labelled data. In this work, we …

One-Dimensional Dilated Hypothesized Learning Method for Intrusion Detection System Under Constraint Resource Environment

B Shuriya, S Umamaheswari… - … on Advancements in …, 2023 - ieeexplore.ieee.org
When a breach is discovered, intrusion detection systems can alert server administrators
and researchers and channel packets for cyber security incidents. In complex systems, these …

Cyber-attack detection in network traffic using machine learning

K Almulla - 2022 - repository.rit.edu
Rapid shifting by government sectors and companies to provide their services and products
over the internet, has immensely increased internet usage by individuals. Through extranets …

Unknown Security Attack Detection of Industrial Control System by Deep Learning

J Wang, P Li, W Kong, R An - Mathematics, 2022 - mdpi.com
With the rapid development of network technologies, the network security of industrial
control systems has aroused widespread concern. As a defense mechanism, an ideal …

Intrusion Detection in Networks using Honey Badger Algorithm with improved Adaptive Neuro-Fuzzy Inference System

IR Alrikabi, MA Alazzawi, A Al-Khaleefa… - 2023 Al-Sadiq …, 2023 - ieeexplore.ieee.org
An Intrusion detection system IDS is a key component of the security management
infrastructure. The goal of IDS is to monitor the processes prevailing in a network and to …

Network Intrusion Detection Based on Feature Selection and Transformer

D Ke - 2023 International Conference on Intelligent …, 2023 - ieeexplore.ieee.org
Network intrusion detection plays an important role in the internet with huge traffic. With the
rise of deep learning, scholars have begun to conduct intrusion detection based on the …

Anomaly detection based on semi-supervised generative adversarial networks

D Liu, L Chen - 2022 2nd International Conference on …, 2022 - ieeexplore.ieee.org
In order to solve the problem of uncivilized speech on campus, a detection method
combining semi-supervised generative adversarial network and self-attention mechanism is …

ENHANCED NETWORK SECURITY: A DATA MINING APPROACH TO INTRUSION DETECTION

TC Hwung, Y Yusof - Journal of Digital System Development, 2024 - e-journal.uum.edu.my
In the ever-evolving landscape of network security, the role of Intrusion Detection Systems
(IDSs) is critical. These systems serve as the guardians of digital networks, defending …

An Industrial and Public Power Grids Malfunction Detection Towards Data Driven

J Singh - 2023 3rd International Conference on Smart …, 2023 - ieeexplore.ieee.org
In this paper, we suggest exploring a concept for distant detection of faulty grid-supporting
equipment utilizing little data. These devices and their auxiliary functions, such reactive …