Results 61 to 70 of about 2,784,569 (167)

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   +1 more source

Deep Learning-Based Intrusion Detection System for Detecting IoT Botnet Attacks: A Review

IEEE Access
The proliferation of Internet of Things (IoT) devices has brought about an increased threat of botnet attacks, necessitating robust security measures. In response to this evolving landscape, deep learning (DL)-based intrusion detection systems (IDS) have
Tamara Al-Shurbaji, Mohammed Anbar, Selvakumar Manickam, Iznan H Hasbullah, Nadia Alfriehat, Basim Ahmad Alabsi, Ahmad Reda Alzighaibi, Hasan Hashim   +7 more
doaj   +1 more source

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

OntoLogX: Ontology‐Guided Knowledge Graph Extraction From Cybersecurity Logs With Large Language Models

Advanced Intelligent Systems, Volume 8, Issue 6, June 2026.
OntoLogX is an autonomous AI agent that uses large language models to transform unstructured cyber security logs into ontology grounded knowledge graphs. By integrating retrieval augmented generation, iterative correction, and a light‐weight log ontology, OntoLogX produces semantically consistent intelligence that links raw log events to MITRE ATT & CK
Luca Cotti, Idilio Drago, Anisa Rula, Devis Bianchini, Federico Cerutti   +4 more
wiley   +1 more source

Semantic Evolution and Consistency Learning for Robust Malicious Network Traffic Detection

Engineering Reports, Volume 8, Issue 6, June 2026.
This paper proposes a semantic evolution and consistency network (SECN) for malicious traffic detection, modeling attack behaviors as temporally evolving semantics. By integrating dual‐level temporal representation and semantic consistency constraints, SECN achieves robust detection and strong generalization under encrypted, cross‐dataset, and unknown ...
Jing Yang, Wei Tan
wiley   +1 more source

MONDEO: Multistage Botnet Detection [PDF]

, 2023
Mobile devices have widespread to become the most used piece of technology. Due to their characteristics, they have become major targets for botnet-related malware. FluBot is one example of botnet malware that infects mobile devices.
Antunes, Nuno, Dias, Duarte, Sousa, Bruno   +2 more
core   +1 more source

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

A Review-Botnet Detection and Suppression in Clouds [PDF]

, 2013
Internet security problems remain a major challenge with many security concerns such as Internet worms, spam, and phishing attacks. Botnets is well-organized distributed network attacks, consist of a large number of bots that generate huge volumes of ...
A. sable, Namrata, Datar, D. S.
core   +1 more source

HSL‐CFS: Hybrid stacked learning with cooperative feature selection for cyberattack detection in smart grids

Energy Conversion and Economics, Volume 7, Issue 3, Page 207-220, June 2026.
Abstract An effective method for detecting cyberattacks is essential to the security of smart grids (SGs). In SGs, data from both cyber and physical domains can support attack detection. However, existing works insufficiently consider the heterogeneity, high dimensionality, and cross‐domain correlations of multi‐source data, affecting model ...
Qize Gao, Qiuyu Lu, June Li, Zhao Peng, Guo Shen, Ming Ni   +5 more
wiley   +1 more source

A Survey of Botnet Architecture and Batnet Detection Techniques

, 2014
[[abstract]]Botnet is an urgent problem that has impact on information security and reduces confidentiality, integrity and availability of certain service.
Cheng-Yi Liu;Chih-Hsiang Peng;Iuon-Chang Lin
core