DoS attack detection in identification of FIR systems with binary-valued observations
From MaRDI portal
Publication:6581073
DOI10.1002/asjc.3005MaRDI QIDQ6581073
Unnamed Author, Ruinan Su, Fengwei Jing, Jin Guo, Yong Song
Publication date: 30 July 2024
Published in: Asian Journal of Control (Search for Journal in Brave)
Related Items (4)
Recursive system identification method from binary input/output measurements ⋮ Distributed maximum correntropy unscented Kalman filter under hybrid attacks in non-Gaussian environment ⋮ Observer-based event-triggered consensus control of nonlinear cyber-physical systems under backlash-like hysteresis and denial-of-service attacks ⋮ Binary observation-based FIR system identification against replay attacks
Cites Work
- Identification of the gain system with quantized observations and bounded persistent excitations
- Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs
- Variational Bayesian approach for ARX systems with missing observations and varying time-delays
- Observer-based detection and identification of sensor attacks in networked CPSs
- Detecting stealthy integrity attacks in a class of nonlinear cyber-physical systems: a backward-in-time approach
- System identification with binary-valued output observations under either-or communication and data packet dropout
- Distributed Krein space-based attack detection over sensor networks under deception attacks
- Recursive projection algorithm on FIR system identification with binary-valued observations
- Interference game for intelligent sensors in cyber-physical systems
- Detection of Denial-of-Service Attacks Based on Computer Vision Techniques
- System Identification With Binary-Valued Observations Under Data Tampering Attacks
- Quantized Identification With Dependent Noise and Fisher Information Ratio of Communication Channels
- Guaranteed cost control of cyber-physical systems with packet dropouts under DoS jamming attacks
This page was built for publication: DoS attack detection in identification of FIR systems with binary-valued observations
