Name
Title | ||
|---|---|---|
A novel trust-based false data detection method for power systems under false data injection attacks |
Abstract | ||
|---|---|---|
This paper proposes a novel trust-based false data detection method for power systems under false data injection attacks (FDIAs). In order to eliminate the interference posed by false data to the power system in the state estimation process, a trust model is first established to estimate the reliability of the system bus. Then an algorithm is proposed to update the bus trust value, when all the trust value of neighbor buses at one bus node are quite low, then this bus is diagnosed as a malicious node and the false data are detected. This method guarantees that the power systems can estimate the state accurately against FDIAs based on the trust of bus. The simulations on the benchmark IEEE 14-bus, IEEE 30-bus and IEEE 57-bus test systems are used to demonstrate the feasibility and effectiveness of proposed algorithm. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.jfranklin.2018.10.030 | Journal of the Franklin Institute |
DocType | Volume | Issue |
Journal | 358 | 1 |
ISSN | Citations | PageRank |
0016-0032 | 0 | 0.34 |
References | Authors | |
21 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Xie | 1 | 0 | 0.34 |
| Chen Peng | 2 | 1881 | 121.56 |
| Minjing Yang | 3 | 0 | 0.34 |
| Xiaobing Kong | 4 | 0 | 0.34 |
| Teng-Fei Zhang | 5 | 18 | 10.99 |