Chained Anomaly Detection Models for Federated Learning: An Intrusion Detection Case Study
The adoption of machine learning and deep learning is on the rise in the cybersecurity domain where these AI methods help strengthen traditional system monitoring and threat detection solutions. However, adversaries too are becoming more effective in concealing malicious behavior amongst large amoun...
Main Authors: | Davy Preuveneers, Vera Rimmer, Ilias Tsingenopoulos, Jan Spooren, Wouter Joosen, Elisabeth Ilie-Zudor |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-12-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/8/12/2663 |
Similar Items
-
Resource Usage and Performance Trade-offs for Machine Learning Models in Smart Environments
by: Davy Preuveneers, et al.
Published: (2020-02-01) -
A Blockchain-Based Federated Forest for SDN-Enabled In-Vehicle Network Intrusion Detection System
by: Ibrahim Aliyu, et al.
Published: (2021-01-01) -
Synergy of Blockchain Technology and Data Mining Techniques for Anomaly Detection
by: Aida Kamišalić, et al.
Published: (2021-08-01) -
Leveraging Battery Usage from Mobile Devices for Active Authentication
by: Jan Spooren, et al.
Published: (2017-01-01) -
Anomaly Based Unknown Intrusion Detection in Endpoint Environments
by: Sujeong Kim, et al.
Published: (2020-06-01)