Privacy-Preserving Synthetic Data Generation Method for IoT-Sensor Network IDS Using CTGAN

Privacy-Preserving Synthetic Data Generation Method for IoT-Sensor Network IDS Using CTGAN

The increased usage of IoT networks brings about new privacy risks, especially when intrusion detection systems (IDSs) rely on large datasets for machine learning (ML) tasks and depend on third parties for storing and training the ML-based IDS. This study proposes a privacy-preserving synthetic data...

Full description

Saved in:
Bibliographic Details
Main Authors: Saleh Alabdulwahab, Young-Tak Kim, Yunsik Son
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Sensors
Subjects:
differential privacy
data utility
generative adversarial network
intrusion detection systems
Internet of things
deep learning
Online Access:https://www.mdpi.com/1424-8220/24/22/7389
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/24/22/7389

Similar Items