Results 41 to 50 of about 958 (168)

La régulation du cybercrime comme alternative à la judiciarisation : le cas des botnets

Criminologie, 2014
Les botnets, ou réseaux d’ordinateurs compromis par des pirates informatiques, représentent à l’heure actuelle la menace criminelle la plus sérieuse, servant de support à la fraude bancaire, aux attaques distribuées par déni de service (DDoS), ou encore ...
Benoît Dupont
doaj   +1 more source

Botnet Defense System: Concept, Design, and Basic Strategy

Information, 2020
This paper proposes a new kind of cyber-security system, named Botnet Defense System (BDS), which defends an Internet of Things (IoT) system against malicious botnets. The concept of BDS is “Fight fire with fire”.
Shingo Yamaguchi
doaj   +1 more source

Botnet Detection in IoT Devices Using Random Forest Classifier with Independent Component Analysis

Journal of ICT, 2022
With rapid technological progress in the Internet of Things (IoT), it has become imperative to concentrate on its security aspect. This paper represents a model that accounts for the detection of botnets through the use of machine learning algorithms ...
Nazmus Sakib Akash, Shakir Rouf, Sigma Jahan, Amlan Chowdhury, Jia Uddin   +4 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

Botnet Identification on Twitter: A Novel Clustering Approach Based on Similarity

IEEE Access
Due to Twitter’s potential reach and influence, malicious automated accounts and services have been operating and growing without control.
Luis Daniel Samper-Escalante, Octavio Loyola-Gonzalez, Raul Monroy, Miguel Angel Medina-Perez   +3 more
doaj   +1 more source

Machine Learning White-Hat Worm Launcher for Tactical Response by Zoning in Botnet Defense System

Sensors, 2022
Malicious botnets such as Mirai are a major threat to IoT networks regarding cyber security. The Botnet Defense System (BDS) is a network security system based on the concept of “fight fire with fire”, and it uses white-hat botnets to fight against ...
Xiangnan Pan, Shingo Yamaguchi
doaj   +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

A Self-Adaptive Deep Learning-Based System for Anomaly Detection in 5G Networks

IEEE Access, 2018
The upcoming fifth-generation (5G) mobile technology, which includes advanced communication features, is posing new challenges on cybersecurity defense systems.
Lorenzo Fernandez Maimo, Angel Luis Perales Gomez, Felix J. Garcia Clemente, Manuel Gil Perez, Gregorio Martinez Perez   +4 more
doaj   +1 more source

Botnet with Browser Extensions [PDF]

2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing, 2011
Botnets are responsible for many large scale organized Internet attacks today. Along with the fight between botnet developers and defenders, the battle field has significantly evolved from traditional centralized IRC to various new approaches, aiming to make bots and command and control channel more and more stealthy.
Lei Liu 0021, Xinwen Zhang, Songqing Chen   +2 more
openaire   +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