Results 61 to 70 of about 1,396 (174)

An Overview of Deep Learning Techniques for Big Data IoT Applications

International Journal of Communication Systems, Volume 39, Issue 4, 10 March 2026.
Reviews deep learning integration with cloud, fog, and edge computing in IoT architectures. Examines model suitability across IoT applications, key challenges, and emerging trends Provides a comparative analysis to guide future deep learning research in IoT environments.
Gagandeep Kaur, Vipin Balyan, Sindhu Hak Gupta   +2 more
wiley   +1 more source

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, Volume 14, Issue 3, Page 1431-1455, March 2026.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

Multi-phase IRC Botnet and Botnet Behavior Detection Model

CoRR, 2015
Botnets are considered one of the most dangerous and serious security threats facing the networks and the Internet. Comparing with the other security threats, botnet members have the ability to be directed and controlled via C&C messages from the botmaster over common protocols such as IRC and HTTP, or even over covert and unknown applications.
Aymen Hasan Rashid Al Awadi, Bahari Belaton   +1 more
openaire   +2 more sources

Detecting P2P botnet based on the role of flows

Tongxin xuebao, 2012
Towards the weaknesses of the existing detection methods of P2P botnet,a novel real-time detection model based on the role of flows was proposed,which was named as RF.According to the characteristics of flows,the model made the flows play the different ...
Yuan-zhang SONG, Jun-ting HE, Bo ZHANG, Jun-jie WANG, An-bang WANG   +4 more
doaj   +2 more sources

Edge‐Oriented DoS/DDoS Intrusion Detection and Supervision Platform

SECURITY AND PRIVACY, Volume 9, Issue 2, March/April 2026.
ABSTRACT This work presents an Edge Node‐Oriented DoS/DDoS Intrusion Detection and Monitoring Platform, a novel anomaly detection system based on temporal analysis with machine learning (ML) and deep learning (DL) algorithms, specifically designed to operate on edge servers with limited resources.
Geraldo Eufrazio Martins Júnior, Thales Guimaraes Marques, Wendley Souza da Silva, Joaquim Celestino Junior   +3 more
wiley   +1 more source

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

BotCatcher:botnet detection system based on deep learning

Tongxin xuebao, 2018
Machine learning technology has wide application in botnet detection.However,with the changes of the forms and command and control mechanisms of botnets,selecting features manually becomes increasingly difficult.To solve this problem,a botnet detection ...
Di WU, Binxing FANG, Xiang CUI, Qixu LIU
doaj   +2 more sources

An Efficient Quantum Enabled Machine Algorithm by Universal Features for Predicting Botnet Attacks in Digital Twin Enabled IoT Networks

Tsinghua Science and Technology
In this manuscript, the authors introduce a quantum enabled Reinforcement Algorithm by Universal Features (REMF) as a lightweight solution designed to identify and assess the impact of botnet attacks on 5G Internet of Things (IoT) networks.
Katta Rajesh Babu, Naramula Venkatesh, K. Shashidhar, Yellampalli Dasaratha Rami Reddy, K. Naga Prakash   +4 more
doaj   +1 more source

Botnet Detection Framework

International Journal of Computer Applications, 2014
Botnet ia a collection on network of bots. i.e the collection of zombie computers which are controlled by a single person or group known as bot master or herder. This paper focuses on botnet detection framework and proposed a generic framework for botnet detection. The proposed framework is based on the approach of passively monitoring network traffic.
Emmanuel Pilli, Anchit Bijalwan, Sanjay Tiwari, Punit Sharma   +3 more
openaire   +1 more source

Pragmatic Study of Botnet Attack Detection In An IoT Environment [PDF]

E3S Web of Conferences
A comprehensive search for primary research published between 2014 and 2023 was carried across several databases. Studies that describe the application of machine learning (ML) and deep learning techniques for if they was carried out across several ...
Vennapureddy Rajasree, Srinivasulu T.
doaj   +1 more source