Results 61 to 70 of about 14,194 (229)

Securing the Unseen: A Comprehensive Exploration Review of AI‐Powered Models for Zero‐Day Attack Detection

Expert Systems, Volume 43, Issue 3, March 2026.
ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam, Nuruzzaman Faruqui, Akm Azad, Mohammad Ali Moni   +3 more
wiley   +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

A Meta-Classification Model for Optimized ZBot Malware Prediction Using Learning Algorithms

Mathematics, 2023
Botnets pose a real threat to cybersecurity by facilitating criminal activities like malware distribution, attacks involving distributed denial of service, fraud, click fraud, phishing, and theft identification.
Shanmugam Jagan, Ashish Ashish, Miroslav Mahdal, Kenneth Ruth Isabels, Jyoti Dhanke, Parita Jain, Muniyandy Elangovan   +6 more
doaj   +1 more source

BotNet Detection on Social Media

, 2021
As our reliance on social media platforms and web services increase day by day, exploiters view these platforms as an opportunity to manipulate our thoughts ad actions. These platforms have become an open playground for social bot accounts. Social bots not only learn human conversations, manners, and presence but also manipulate public opinion, act as ...
Devle, Aniket Chandrakant, Jose, Julia Ann, Saraswathula, Abhay Shrinivas, Mehta, Shubham, Srivastava, Siddhant, Kona, Sirisha, Daggumalli, Sudheera   +6 more
openaire   +2 more sources

OnionBots: Subverting Privacy Infrastructure for Cyber Attacks

, 2015
Over the last decade botnets survived by adopting a sequence of increasingly sophisticated strategies to evade detection and take overs, and to monetize their infrastructure. At the same time, the success of privacy infrastructures such as Tor opened the
Noubir, Guevara, Sanatinia, Amirali
core   +1 more source

A Two‐Phase Detection Method Based on Ensemble Feature Fusion for Detecting Distributed Denial of Service (DDoS) Attacks in Cloud Computing Using Deep Learning Algorithm

Engineering Reports, Volume 8, Issue 2, February 2026.
This study introduces a two‐phase method for detecting DDoS attacks in cloud environments using ensemble feature fusion and a hybrid CNN‐LSTM model. By combining meta‐heuristic feature selection with deep learning, the approach achieves over 99% accuracy on benchmark datasets, reducing false positives and improving cybersecurity resilience.
Hind Saad Hussein, Fahad Navabifar, Fariba Majidi, Hayder Kadhim Hammood   +3 more
wiley   +1 more source

A Systematic Literature Review: Classifying IoT Botnet Data Features Based on Its Lifecycle

IEEE Access
As the Internet of Things (IoT) becomes increasingly indispensable across various domains, the connectivity between humans, machines, and devices intensifies.
Shihao Liu, Fariza Fauzi, Ven Jyn Kok
doaj   +1 more source

Exploiting Vision Transformer and Ensemble Learning for Advanced Malware Classification

Engineering Reports, Volume 8, Issue 1, January 2026.
Overview of the proposed RF–ViT ensemble for multi‐class malware classification. Textual (BoW/byte‐frequency) and visual representations are combined via a product rule, achieving improved accuracy and robustness over individual models. ABSTRACT Malware remains a significant concern for modern digital systems, increasing the need for reliable and ...
Fadi Makarem, Rida El Chall, Abed Ellatif Samhat, Khouloud Samrouth, Nader Bakir   +4 more
wiley   +1 more source

Investigating the Agility Bias in DNS Graph Mining

, 2017
The concept of agile domain name system (DNS) refers to dynamic and rapidly changing mappings between domain names and their Internet protocol (IP) addresses.
Leppänen, Ville, Ruohonen, Jukka
core   +1 more source