Book contents
- Frontmatter
- Contents
- List of Contributors
- Preface
- Part I Statistical Learning
- Part II Data-Driven Anomaly Detection
- 5 Quickest Detection and Isolation of Transmission Line Outages
- 6 Active Sensing for Quickest Anomaly Detection
- 7 Random Matrix Theory for Analyzing Spatio-Temporal Data
- 8 Graph-Theoretic Analysis of Power Grid Robustness
- Part III Data Quality, Integrity, and Privacy
- Part IV Signal Processing
- Part V Large-Scale Optimization
- Part VI Game Theory
- Index
8 - Graph-Theoretic Analysis of Power Grid Robustness
from Part II - Data-Driven Anomaly Detection
Published online by Cambridge University Press: 22 March 2021
Book contents
- Frontmatter
- Contents
- List of Contributors
- Preface
- Part I Statistical Learning
- Part II Data-Driven Anomaly Detection
- 5 Quickest Detection and Isolation of Transmission Line Outages
- 6 Active Sensing for Quickest Anomaly Detection
- 7 Random Matrix Theory for Analyzing Spatio-Temporal Data
- 8 Graph-Theoretic Analysis of Power Grid Robustness
- Part III Data Quality, Integrity, and Privacy
- Part IV Signal Processing
- Part V Large-Scale Optimization
- Part VI Game Theory
- Index
Summary
This chapter focuses on critical infrastructures in the power grid, which often rely on Industrial Control Systems (ICS) to operate and are exposed to vulnerabilities ranging from physical damage to injection of information that appears to be consistent with industrial control protocols. This way, infiltration of firewalls protecting the control perimeter of the control network becomes a significant tread. The goal of this chapter is to review identification and intrusion detection algorithms for protecting the power grid, based on the knowledge of the expected behavior of the system.
- Type
- Chapter
- Information
- Advanced Data Analytics for Power Systems , pp. 175 - 194Publisher: Cambridge University PressPrint publication year: 2021