Efficient detection of faults and false data injection attacks in smart grid using a reconfigurable Kalman filter
- Title
- Efficient detection of faults and false data injection attacks in smart grid using a reconfigurable Kalman filter
- Creator
- Dayananda P.; Srikantaswamy M.; Nagaraju S.; Velluri R.; Kumar D.M.
- Description
- The distribution denial of service (DDoS) attack, fault data injection attack (FDIA) and random attack is reduced. The monitoring and security of smart grid systems are improved using reconfigurable Kalman filter. Methods: A sinusoidal voltage signal with random Gaussian noise is applied to the Reconfigurable Euclidean detector (RED) evaluator. The MATLAB function randn() has been used to produce sequence distribution channel noise with mean value zero to analysed the amplitude variation with respect to evolution state variable. The detector noise rate is analysed with respect to threshold. The detection rate of various attacks such as DDOS, Random and false data injection attacks is also analysed. The proposed mathematical model is effectively reconstructed to frame the original sinusoidal signal from the evaluator state variable using reconfigurable Euclidean detectors. 2022, Institute of Advanced Engineering and Science. All rights reserved.
- Source
- International Journal of Power Electronics and Drive Systems, Vol-13, No. 4, pp. 2086-2097.
- Date
- 2022-01-01
- Publisher
- Institute of Advanced Engineering and Science
- Subject
- False data injection attack; Kalman filter; Random attack; Reconfigurable Euclidean detector; Smart grid
- Coverage
- Dayananda P., Department of Electrical and Electronics Engineering, SJB Institute of Technology, Bangalore, India; Srikantaswamy M., Department of Electronics and Communication Engineering, JSS Academy of Technical Education, Bangalore, India; Nagaraju S., Department of Electrical and Electronics Engineering, Sri Jayachamarajendra College of Engineering, Mysore, India; Velluri R., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bengaluru, India; Kumar D.M., Department of Electronics and Instrumentation Engineering, JSS Academy of Technical Education, Bangalore, India
- Rights
- All Open Access; Gold Open Access; Green Open Access
- Relation
- ISSN: 20888694
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Dayananda P.; Srikantaswamy M.; Nagaraju S.; Velluri R.; Kumar D.M., “Efficient detection of faults and false data injection attacks in smart grid using a reconfigurable Kalman filter,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/15280.