Abstract
Cyber-physical attacks are the main substantial threats facing the utilization and development of the various smart grid technologies. Among these attacks, false data injection attack represents a main category with its widely varied types and impacts that have been extensively reported recently. In addressing this threat, several detection algorithms have been developed in the last few years. These were either model-based or data-driven algorithms. This paper provides an intensive summary of these algorithms by categorizing them and elaborating on the pros and cons of each category. The paper starts by introducing the various cyber-physical attacks along with the main reported incidents in history. The significance and the impacts of the false data injection attacks are then reported. The concluding remarks present the main criteria that should be considered in developing future detection algorithms for the false data injection attacks. © 2019 IEEE.
| Original language | English |
|---|---|
| Pages (from-to) | 2218-2234 |
| Journal | IEEE Transactions on Smart Grid |
| Volume | 11 |
| Issue number | 3 |
| Online published | 30 Oct 2019 |
| DOIs | |
| Publication status | Published - May 2020 |
| Externally published | Yes |
Research Keywords
- Cyber-physical attacks
- data-driven detection algorithms
- false data injection
- machine learning
- model-based detection algorithms
- smart grid
- state estimation
- stealth attacks
Policy Impact
- Cited in Policy Documents
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