A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems-Reference-Cited by-同舟云学术

A Bayesian Deep Learning Approach With Convolutional Feature Engineering to Discriminate Cyber-Physical Intrusions in Smart Grid Systems

Author:

Kaur Devinder¹,Anwar Adnan²^ORCID,Kamwa Innocent³^ORCID,Islam Shama¹^ORCID,Muyeen S. M.⁴^ORCID,Hosseinzadeh Nasser¹^ORCID

Affiliation:

1. School of Engineering, Deakin University, Geelong, VIC, Australia

2. Centre for Cyber Security Research and Innovation (CSRI), School of Information Technology, Deakin University, Geelong, VIC, Australia

3. Department of Electrical Engineering and Computer Engineering, Laval University, Quebec City, Canada

4. Department of Electrical Engineering, Qatar University, Doha, Qatar

Funder

Faculty of Science, Engineering and Built Environment, Deakin University, under the Mini Australian Research Council (ARC) Analog Program

Laval University from the Canada National Sciences and Engineering Research Council

Qatar National Library

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference43 articles.

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