Results 91 to 100 of about 20,777 (211)
Digital Agriculture: Past, Present, and Future
Advanced Intelligent Discovery, Volume 2, Issue 1, February 2026.Digital agriculture integrates Internet of Things, artificial intelligence, and blockchain to enhance efficiency and sustainability in farming. This review outlines its evolution, current applications, and future directions, highlighting both technological advances and key challenges for global implementation.
Xiaoding Wang +3 more
wiley +1 more source
Meta Reinforcement Learning for Automated Cyber Defence
Applied AI Letters, Volume 7, Issue 1, February 2026.ABSTRACT Reinforcement learning (RL) solutions have shown considerable promise for automating the defense of networks to cyber attacks. However, a limitation to their real world deployment is the sample efficiency and generalizability of RL agents. This means that even small changes to attack types require a new agent to be trained from scratch.
Andrew Thomas, Nick Tillyer
wiley +1 more source
Network Protection Against DDoS Attacks
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems, 2015 The paper deals with possibilities of the network protection against Distributed Denial of Service attacks (DDoS). The basic types of DDoS attacks and their impact on the protected network are presented here.
Petr Dzurenda +2 more
doaj +1 more source
Distinguishing DDoS attacks from flash crowds using probability metrics
, 2009 Both Flash crowds and DDoS (Distributed Denial-of-Service) attacks have very similar properties in terms of internet traffic, however Flash crowds are legitimate flows and DDoS attacks are illegitimate flows, and DDoS attacks have been a serious threat ...
Hai, Jing +4 more
core +1 more source
An Efficient Detection Mechanism for Distributed Denial of Service (DDoS) Attack
CoRR, 2013 arXiv admin note: substantial text overlap with arXiv:1103.3333, arXiv:1101.2715 by other ...
Saravanan Kumarasamy, R. Asokan
openaire +2 more sources
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 +3 more
wiley +1 more source
JUTI: Jurnal Ilmiah Teknologi Informasi, 2015 Denial of Service (DoS) merupakan permasalahan keamanan jaringan yang sampai saat ini terus berkembang secara dinamis. Semakin tinggi kemampuan komputasi suatu komputer penyerang, serangan DoS yang dapat dihasilkan juga semakin membahayakan. Serangan ini
Septian Geges, Waskitho Wibisono
doaj +1 more source
Distributed Denial of Service (DDoS) Protection in Cloud Infrastructure
, 2019 This study investigates the Distributed Denial of Service (DDoS) protection techniques with the cloud infrastructure and analyses implementation and effectiveness challenges. This research paper aims to evaluate and analyze the DDoS protection techniques within the cloud infrastructure for increasing security and mitigating attacks.
openaire +1 more source
Feature-Selection-Based DDoS Attack Detection Using AI Algorithms
TelecomSDN has the ability to transform network design by providing increased versatility and effective regulation. Its programmable centralized controller gives network administration employees more authority, allowing for more seamless supervision.
Muhammad Saibtain Raza +3 more
doaj +1 more source
A Novel DDoS Attack Detection Based on Gaussian Naive Bayes [PDF]
, 2017 Distributed Denial of Service (DDoS) is a type of attack using the volume, intensity, and more costs mitigation to increase in this era. Attackers used many zombie computers to exhaust the resources available to a network, application or service so that ...
Aji, S. (Sukma) +2 more
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