Sparse Malicious False Data Injection Attacks and Defense Mechanisms in Smart Grids
- Submitting institution
-
University of Keele
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 363
- Type
- D - Journal article
- DOI
-
10.1109/TII.2015.2475695
- Title of journal
- IEEE Transactions on Industrial Informatics
- Article number
- -
- First page
- 1
- Volume
- 11
- Issue
- 5
- ISSN
- 1551-3203
- Open access status
- Out of scope for open access requirements
- Month of publication
- September
- Year of publication
- 2015
- URL
-
https://ieeexplore.ieee.org/document/7234893
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 78
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is one of the first papers to address the problem of detecting false data injection attacks on smart grids. The research was supported by a Dorothy Hodgkin Postgraduate Award and CASE Studentship (Toshiba and Bristol), and is widely cited in smart grid cybersecurity. An enhanced version of the paper also appears as chapter 10 of the IET Digital Library reference book on Smart Energy (2016: https://doi.org/fgdq; ebook: IET power and energy series, 88). More recently, Fan's research contributed to his invitation to be Keele CoI on EPSRC EnergyREV consortium (EP/S031863/1), where he is cybersecurity lead (WP1).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -