Results 61 to 70 of about 3,020 (212)

Generating Pattern‐Based Datasets for Cyber Attack Detection Using Machine‐Learning Techniques

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.
The aim of this work is to review the state of the art in the design, generation, and labeling of attack pattern datasets for training of detection systems based on machine learning. ABSTRACT This work aims to review the state of the art in the design, generation, and labeling of attack pattern datasets for the training of detection systems based on ...
Pedro Díaz García, Diego López Abril, Javier Bermejo Higuera, Víctor Gonzalez Llorente, Miguel Angel Sicilia Urbán   +4 more
wiley   +1 more source

Visual analytics with decision tree on network traffic flow for botnet detection [PDF]

, 2018
Visual analytics (VA) is an integral approach combining visualization, human factors, and data analysis. VA can synthesize information and derive insight from massive, dynamic, ambiguous and often conflicting data.
Ismail, Saiful Adli, Amir Sjarif, Nilam Nur, Che Mohd. Yusof, Rasimah, Ya’acob, Suraya, Mohd. Azmi, Nurulhuda Firdaus, Muhammad, Muhammad Khairul Rijal   +5 more
core  

Botnet Detection Using Recurrent Variational Autoencoder

, 2020
Botnet detection is an active research topic as botnets are a source of many malicious activities, including distributed denial-of-service (DDoS), click-fraud, spamming, and crypto-mining attacks.
Sim, Alex, Kim, Jinoh, Jeeyung Kim, Jinoh Kim, Alex Sim, Kesheng Wu, Kim, Jeeyung, Wu, Kesheng   +7 more
core   +1 more source

Abnormal Traffic Detection Method for Multi-stage Attacks of Internet of Things Botnets [PDF]

Jisuanji kexue
To address the problem of how to efficiently detect multi-stage attack behavior of IoT botnet from massive network traffic data,an IoT botnet attack detection method based on multi-scale hybrid residual network(IBAD-MHRN)is proposed.Firstly,in order to ...
CHEN Liang, LI Zhihua
doaj   +1 more source

IoT Botnet Attack Detection Based on Optimized Extreme Gradient Boosting and Feature Selection

Sensors, 2020
Nowadays, Internet of Things (IoT) technology has various network applications and has attracted the interest of many research and industrial communities.
Mnahi Alqahtani, Hassan Mathkour, Mohamed Maher Ben Ismail   +2 more
doaj   +1 more source

AI‐Powered Anomaly Detection for Secure Internet of Things (IoT): Optimising XGBoost and Deep Learning With Bayesian Optimisation

CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 447-463, April 2026.
ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim, Lal Hussain, Mohammed A. Alqarni, Faisal S. Alsubaei, Rasha Jamal Atwah   +4 more
wiley   +1 more source

Botnet Campaign Detection on Twitter

CoRR, 2018
This is an approach to detecting a subset of bots on Twitter, that at best is under-researched. This approach will be generic enough to be adaptable to most, if not all social networks. The subset of bots this focuses on are those that can evade most, if not all current detection methods.
openaire   +2 more sources

BotCloud: Detecting botnets using MapReduce [PDF]

2011 IEEE International Workshop on Information Forensics and Security, 2011
Botnets are a major threat of the current Internet. Understanding the novel generation of botnets relying on peer-to-peer networks is crucial for mitigating this threat. Nowadays, botnet traffic is mixed with a huge volume of benign traffic due to almost ubiquitous high speed networks.
Jérôme François, Shaonan Wang, Walter Bronzi, Radu State, Thomas Engel 0001   +4 more
openaire   +1 more source

A proposed framework for P2P botnet detection [PDF]

, 2010
Botnet is most widespread and occurs commonly in today‘s cyber attacks, resulting in serious threats to our network assets and organization’s properties.
Abdul Manaf, Azizah, Chaeikar, Saman Shojae, Ahmad, Rabiah, Zamani, Mazdak, Zeidanloo, Hossein Rouhani   +4 more
core   +1 more source

Robust and Noise-Resilient Botnet Detection Framework Using Heterogeneous Radial Basis Function Neural Network

Applied Sciences
The rapid evolution of botnet attacks poses a critical challenge facing cybersecurity, necessitating the development of intrusion detection models that are both highly accurate and computationally efficient.
Lama Awad, Sherenaz Al-Haj Baddar, Azzam Sleit   +2 more
doaj   +1 more source