Browsing by Author "Khan, Imtiaj"
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- Assessment of Cyber Vulnerabilities and Countermeasures for GPS-Time Synchronized Measurements in Smart GridsKhan, Imtiaj (Virginia Tech, 2024-07-02)We aim at expanding the horizon of existing research on cyberattacks against the time-syncrhonized devices such as PMUs and PDCs, along with corresponding countermeasures. We develop a PMU-PDC cybersecurity testbed at Virginia Tech Power and Energy Center (PEC) lab. The testbed is able to simulate real-world GPS-spoofing attack (GSA) and false data injection attack (FDIA) scenarios. Moreover, the testbed can incorporates cyberattack detection algorithm in pseudo real-time. After that, we propose three stealthy attack scenarios that exploit the vulnerabilities of time-synchronization for both PMU and PDC. The next part of this dissertation is the enhancement of Hankel-matrix based bad data detection model. The existing general Hankel-matrix based bad data detection model provide satisfactory performance. However, it fails in differentiating GPS-spoofing attack from FDIA. We propose an enhanced phase angle Hankel-matrix model that can conclusively identify GPS-spoofing attack. Furthermore, we reduce the computational burden for Hankel-matrix based bad data and cyberattack detection models. Finally, we verify the effectiveness of our enhanced Hankel-matrix model for proposed stealthy attack scenarios.
- Real-Time Detection of GPS Spoofing Attack with Hankel Matrix and Unwrapped Phase Angle DataKhan, Imtiaj (Virginia Tech, 2021-11)Cyber-attack on synchrophasor data has become a widely explored area. However, GPS-spoofing and FDIA attacks require different responsive actions. State-estimation based attack detection method works similar way for both types of attacks. It implies that using state-estimation based detection alone doesn’t give the control center enough information about the attack type. This scenario is specifically more critical for those attack detection methods which consider GPS-spoofing attack as another FDIA with falsified phase angle data. Since identifying correct attack type is paramount, we have attempted to develop an algorithm to distinguish these two attacks. Previous researchers exploited low-rank approximation of Hankel Matrix to differentiate between FDIA and physical events. We have demonstrated that, together with angle unwrapping algorithm, low-rank approximation of Hankel Matrix can help us separating GPS-spoofing attack with FDIA. The proposed method is verified with simulation result. It has been demonstrated that the GSA with 3 second time-shift creates a low-rank approximation error 700% higher than that of normal condition, whereas FDIA doesn’t produce any significant change in low-rank approximation error from that of normal condition. Finally, we have proposed a real-time method for successful identification of event, FDIA and GSA.