Countering targeted cyber-physical attacks using anomaly detection in self-adaptive Industry 4.0 Systems

2018 ◽  
Vol 135 (3) ◽  
pp. 278-285 ◽  
Author(s):  
Giuseppe Settanni ◽  
Florian Skopik ◽  
Markus Wurzenberger ◽  
Roman Fiedler
Keyword(s):  
Anomaly Detection ◽  
Industry 4.0 ◽  
Self Adaptive

scholarly journals PulSec: Secure Element based framework for sensors anomaly detection in Industry 4.0

2019 ◽  
Vol 52 (13) ◽  
pp. 1204-1209 ◽  
Author(s):  
Varun Deshpande ◽  
Laurent George ◽  
Hakim Badis
Keyword(s):  
Anomaly Detection ◽  
Industry 4.0 ◽  
Secure Element

Anomaly detection via blockchained deep learning smart contracts in industry 4.0

2020 ◽  
Vol 32 (23) ◽  
pp. 17361-17378
Author(s):  
Konstantinos Demertzis ◽  
Lazaros Iliadis ◽  
Nikos Tziritas ◽  
Panagiotis Kikiras
Keyword(s):  
Deep Learning ◽  
Anomaly Detection ◽  
Industry 4.0 ◽  
Smart Contracts

Self-adaptive and dynamic clustering for online anomaly detection

2011 ◽  
Vol 38 (12) ◽  
pp. 14891-14898 ◽  
Author(s):  
Seungmin Lee ◽  
Gisung Kim ◽  
Sehun Kim
Keyword(s):  
Anomaly Detection ◽  
Dynamic Clustering ◽  
Online Anomaly Detection ◽  
Self Adaptive

scholarly journals Remote Anomaly Detection in Industry 4.0 Using Resource-Constrained Devices

2021 ◽  
Author(s):  
Anders E. Kalor ◽  
Daniel Michelsanti ◽  
Federico Chiariotti ◽  
Zheng-Hua Tan ◽  
Petar Popovski
Keyword(s):  
Anomaly Detection ◽  
Industry 4.0 ◽  
Resource Constrained ◽  
Resource Constrained Devices ◽  
Constrained Devices

Anomaly detection in non-stationary data: Ensemble based self-adaptive OCSVM

2016 ◽  
Author(s):  
Zahra Ghafoori ◽  
Sarah M. Erfani ◽  
Sutharshan Rajasegarar ◽  
Shanika Karunasekera ◽  
Christopher A. Leckie
Keyword(s):  
Anomaly Detection ◽  
Self Adaptive
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