Mitigating Against a Succession of Hidden Failure Accelerants Involved in an Insider Threat Sequential Topology Attack on a Smart Grid: Devising a Defensive Paradigm via a Bespoke Convolutional Adversarial Neural Network Module and Particle Swarm Optimization-based Enhanced Reinforcement Learning Component

Steve Chan

doi:10.2139/ssrn.4287248

Mitigating Against a Succession of Hidden Failure Accelerants Involved in an Insider Threat Sequential Topology Attack on a Smart Grid: Devising a Defensive Paradigm via a Bespoke Convolutional Adversarial Neural Network Module and Particle Swarm Optimization-based Enhanced Reinforcement Learning Component

Steve Chan

https://doi.org/10.2139/ssrn.4287248

Copy DOI

Export

Save

Cite

Journal: SSRN Electronic Journal	Publication Date: Jan 1, 2022
Citations: 1

Affiliation: Institute of Electrical and Electronics Engineers, Harvard University Press

#Neural Network Particle Swarm #Network Particle Swarm #Smart Grid #Sequential Attack #Neural Module #Enhanced Reinforcement Learning #Swarm Optimization-based #Adversarial Neural Network #Particle Swarm Optimization-based #Sequential Topology

Abstract
Full-Text
Similar Papers

Abstract

Listen

Mitigating Against a Succession of Hidden Failure Accelerants Involved in an Insider Threat Sequential Topology Attack on a Smart Grid: Devising a Defensive Paradigm via a Bespoke Convolutional Adversarial Neural Network Module and Particle Swarm Optimization-based Enhanced Reinforcement Learning Component

Full Text

Published Version

Check institute access

Open DOI Link

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Similar Papers

Paper Title

Journal

Date

Author

View more papers

More From: SSRN Electronic Journal

Paper Title

Journal

Date

Author

View more papers

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.

R Discovery Prime