Open-Set Recognition in Unknown DDoS Attacks Detection with Reciprocal Points Learning

CS Shieh, FA Ho, MF Horng, TT Nguyen… - IEEE …, 2024 - ieeexplore.ieee.org
The internet, a cornerstone of modern life, has profound implications across personal,
business, and society. However, its widespread use has posed challenges, especially …

One-Parameter Statistical Methods to Recognize DDoS Attacks

R Hajtmanek, M Kontšek, J Smieško, J Uramová - Symmetry, 2022 - mdpi.com
Within our academic high-speed network infrastructure which is used for connecting all
universities and high schools in our country to the Internet, there are thousands of …

Generating practical adversarial examples against learning-based network intrusion detection systems

V Kumar, K Kumar, M Singh - Annals of Telecommunications, 2024 - Springer
There has been a significant development in the design of intrusion detection systems (IDS)
by using deep learning (DL)/machine learning (ML) methods for detecting threats in a …

Detection of phishing URLs with deep learning based on GAN-CNN-LSTM network and swarm intelligence algorithms

AJS Albahadili, A Akbas, J Rahebi - Signal, Image and Video Processing, 2024 - Springer
Phishing attacks are one of the challenges of the Internet and its users. Phishing attacks are
an example of social engineering attacks based on deceiving users. In phishing attacks …

Machine Recognition of DDoS Attacks Using Statistical Parameters

J Smiesko, P Segec, M Kontsek - Mathematics, 2023 - mdpi.com
As part of the research in the recently ended project SANET II, we were trying to create a
new machine-learning system without a teacher. This system was designed to recognize …

Analyzing the Evolution of DDoS Attack Detection: Traditional vs. Modern Machine Learning Models

V Premanand, SS Gokulnath… - … on Recent Trends in …, 2023 - ieeexplore.ieee.org
Distributed Denial of Service (DDoS) attacks continue to pose a significant threat to network
and system security. This research explores the transition from traditional to modern …

Reciprocal Points Learning Based Unknown DDoS Attacks Detection

FA Ho, CS Shieh, MF Horng, TT Nguyen… - Asian Conference on …, 2023 - Springer
In recent years, the increasing reliance on Internet services has made the Internet an
integral part of our daily life. The COVID-19 pandemic has further accelerated this trend by …

Double Reinforcement Learning Based Interactive GAN for Detection of Volumetric Attacks in Cloud Computing

K Bhargavi - 2023 IEEE Fifth International Conference on …, 2023 - ieeexplore.ieee.org
The rapid growth of cloud computing has increased the risk of volumetric attacks on cloud
infrastructure. This research paper proposes a comprehensive approach to detect such …

DDOS DEFENSE SIMULATION USING IPTABLES FIREWALL ON UBUNTU

R Ariza, C Hidayat, HI Amrullah… - Novice Research …, 2024 - eksplorasi.org
Distributed Denial of Service (DDoS) attacks pose significant threats to network security and
service availability by overwhelming targets with excessive traffic. This article presents a …

[PDF][PDF] Defenses for Adversarial attacks in Network Intrusion Detection System–A Survey

N Dhinakaran, S Anto - pdfs.semanticscholar.org
In computer security, machine learning has a greater impact in recent years. Ranging from
spam filtering, malware analysis, and traffic analysis to network security the usage of …