A Multimodal Framework for Advanced Cybersecurity Threat Detection Using GAN-Driven Data Synthesis

A Multimodal Framework for Advanced Cybersecurity Threat Detection Using GAN-Driven Data Synthesis

Cybersecurity threats are becoming increasingly sophisticated, frequent, and diverse, posing a major risk to critical infrastructure, public trust, and digital economies. Traditional intrusion detection systems often struggle with detecting novel or rare attack types, particularly when data availabi...

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Bibliographic Details
Main Authors: Nikolaos Peppes, Emmanouil Daskalakis, Theodoros Alexakis, Evgenia Adamopoulou
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Applied Sciences
Subjects:
threat detection
cybersecurity
synthetic data generation
generative adversarial networks (GANs)
multimodal fusion
deep learning
Online Access:https://www.mdpi.com/2076-3417/15/15/8730
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