Results 81 to 90 of about 20,777 (211)

AI‐Powered Anomaly Detection for Secure Internet of Things (IoT): Optimising XGBoost and Deep Learning With Bayesian Optimisation

CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 447-463, April 2026.
ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim, Lal Hussain, Mohammed A. Alqarni, Faisal S. Alsubaei, Rasha Jamal Atwah   +4 more
wiley   +1 more source

Adaptive DDoS attack detection via packet payload feature selection

Cybersecurity
Distributed Denial of Service attacks (DDoS) are a common and influential network malicious behavior. The timely and accurate detection of Distributed Denial-of-Service (DDoS) attacks constitutes a critically significant research imperative in cyber ...
Fengjun Zhang, Yong Cui, Guangcan Cui, Lisheng Huang, Qinghua Li, Kai Shi, Yunhai Lan   +6 more
doaj   +1 more source

Detecting DDoS attacks using machine learning algorithms and feature selection methods [PDF]

International Journal of Data and Network Science
A Distributed Denial of Service (DDoS) attack occurs when an attacker tries to disrupt a network, service or website by flooding huge numbers of packets on the internet traffic.
Mohammed Amin Almaiah, Rana Alrawashdeh, Tayseer Alkhdour, Romel Al-Ali, Gaith Rjoub , Theyazan Aldahyani   +5 more
doaj   +1 more source

MLDAS: Machine Learning Dynamic Algorithm Selection for Software‐Defined Networking Security

Concurrency and Computation: Practice and Experience, Volume 38, Issue 5, March 2026.
ABSTRACT Network security is a critical concern in the digital landscape of today, with users demanding secure browsing experiences and protection of their personal data. This study explores the dynamic integration of Machine Learning (ML) algorithms with Software‐Defined Networking (SDN) controllers to enhance network security through adaptive ...
Pablo Benlloch, Oscar Romero, Antonio Leon, Jaime Lloret   +3 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

A real-time machine-learning model for detecting and mitigating DDoS attacks

Cybersecurity
Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks are among the most lethal cyber threats in this world, which make an online service unavailable to its legitimate users by overwhelming the service provider’s resources.
Mohammad Fathian, Alireza Seifousadati
doaj   +1 more source

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

Deteksi Serangan DDoS Menggunakan Neural Network dengan Fungsi Fixed Moving Average Window

JISKA (Jurnal Informatika Sunan Kalijaga), 2017
Distributed denial-of-service (DDoS) merupakan jenis serangan dengan volume, intensitas, dan biaya mitigasi yang terus meningkat seiring berkembangnya skala organisasi.
Arif Wirawan Muhammad, Imam Riadi, Sunardi Sunardi   +2 more
doaj   +1 more source

A Study of DDOS (Distributed-denial-of- service) Attacks and Its Preventions

International Journal of Scientific Research in Science, Engineering and Technology, 2020
<p>The data security is one of the most important themes in the information World. Cloud Computing is a grooving technology and implemented by many companies, but there are many issues and one of them is DDOS. .The DDOS attack is one of the most Threatening attacks in today’s world.
Bhawna Tripathi, Devesh Katiyar, Gaurav Goel   +2 more
openaire   +1 more source

Real‐Time Detection and Prevention of DoS Attack in Unmanned Marine Vehicles Using Machine Learning

SECURITY AND PRIVACY, Volume 9, Issue 2, March/April 2026.
ABSTRACT Unmanned marine vehicles (UMVs) are one of the most crucial components of the underwater communication and surveillance system in the marine and oceanographic environment. This research introduces a novel approach to stabilize the connection in an unstable underwater environment by inheriting features of communication velocities.
Noman Ali, Yousaf Saeed, Muhammad Ibrahim, Muhammad Bilal, Muhammad Tahir, Muhammad Aslam, Edore Akpokodje, Syeda Fizzah Jilani, Meng Tang   +8 more
wiley   +1 more source