IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (IEEE SmartGridComm 2020)

Session Opening-remarks-2: Opening Remarks Session Keynote-2: Keynote 2
Session A2: Analytics 2: Machine Learning for Grid Operations Session C2: Control 2: Advanced Controls Session N2: Networking 2: Communications for Distributed System Management Session A3: Analytics 3: Data Analytics for Grid I Session IS-3: Invited 3: Electricity Markets Session S3: Security 3: Attack and Defence Session IS-4: Invited 4: Energy Storage and DER Session WAEG2: Workshop on Autonomous Energy Grid: A Distributed Optimization and Control Perspective 2
Session Tutorial-1: Stochastic Models and Optimization Techniques for Efficient Integration of Electric Vehicles in Smart Grids Session Tutorial-2: Power System Machine Learning Applications: From physics-informed learning for decision support to inference at the edge for control

Keynote Talks

Session Opening-remarks-2

Opening Remarks

Conference
2:00 PM — 2:10 PM UTC
Local
Nov 12 Thu, 9:00 AM — 9:10 AM EST
Session Chair

Klara Nahrstedt (UIUC) & Oliver Kosut (ASU) <br> Zoom Room Host(s): Lamia Varawala, Ezzeldin Shereen (KTH)

Session Keynote-2

Keynote 2

Conference
2:10 PM — 3:00 PM UTC
Local
Nov 12 Thu, 9:10 AM — 10:00 AM EST

Analytics-Driven Cyber-Physical Security for a Converged Smart Grid

Deepa Kundur (U. Toronto)

6
The field of cyber-physical security has evolved greatly over the last decade especially in the context of critical infrastructures such as the smart grid. The current challenges aim to address the increased sophistication of cyberattacks in the context of a more automated grid. Emerging polymorphic and stealthy attacks necessitate more coordinated and intelligent approaches to mitigation. In addition to the typical defence-in-depth paradigm, more harmonized protection and resilience strategies are essential. Development of next-generation tools for cyber-physical security requires the adoption of effective models that are compatible with salient trends in smart grid infrastructure including Information Technology/Operational Technology (IT/OT) convergence. The resulting data-rich cyber-physical environment from IT/OT convergence suggests a strong need for greater data-driven modelling paradigms and analytics. In this talk, we provide examples of deep learning in the context of anomaly detection for the cyber-physical protection of transmission protection systems. We then present a brave new world of opportunities for smart grid cyber-physical security using a data analytics-driven approach.
Session Chair

Klara Nahrstedt (UIUC) <br> Zoom Room Host(s): Lamia Varawala, Ezzeldin Shereen (KTH)

Made with in Toronto · Privacy Policy · © 2022 Duetone Corp.