A Multi-Branched Hybrid Perceptron Network for DDoS Attack Detection Using Dynamic Feature Adaptation and Multi-Instance Learning

A Multi-Branched Hybrid Perceptron Network for DDoS Attack Detection Using Dynamic Feature Adaptation and Multi-Instance Learning

The increasing sophistication and frequency of Distributed Denial of Service (DDoS) attacks necessitate advanced detection systems. These attacks leave networks vulnerable to disruptions, resource overload, security breaches, and financial losses. Conventional detection systems suffer from high fals...

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Bibliographic Details
Main Authors: Ali Tariq Kalil Al-Khayyat, Osman Nuri Ucan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
DDoS attacks
hybrid perceptron network
multi-instance learning
false positives
network traffic analysis
Online Access:https://ieeexplore.ieee.org/document/10810438/
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