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Syed Shafiulla

dblp:403/8444 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0006-7785-8947ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Cyber-physical and IoT security · 67% Network security · 33%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Energy systems and smart grids · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network security › intrusion detection and prevention › intrusion detection
attack detection
0.912025
A Dynamic State Estimation-Based Cyberattack Detection Scheme to Supervise Legacy Pilot Protection Operation · IEEE Trans. Inf. Forensics Secur. 2025
Cyber-physical and IoT security › smart grid security
false data injection attack detection
0.912025
A Dynamic State Estimation-Based Cyberattack Detection Scheme to Supervise Legacy Pilot Protection Operation · IEEE Trans. Inf. Forensics Secur. 2025
Cyber-physical and IoT security
smart grid security
0.912025
A Dynamic State Estimation-Based Cyberattack Detection Scheme to Supervise Legacy Pilot Protection Operation · IEEE Trans. Inf. Forensics Secur. 2025
Energy systems and smart grids › power system automation
substation automation
0.312025
A Dynamic State Estimation-Based Cyberattack Detection Scheme to Supervise Legacy Pilot Protection Operation · IEEE Trans. Inf. Forensics Secur. 2025

Methods — techniques the papers use, named apart from their topics

unscented kalman filter · 1.7dynamic state estimation · 1.7
YearPublicationVenuePosition
2025 A Dynamic State Estimation-Based Cyberattack Detection Scheme to Supervise Legacy Pilot Protection Operation
abstract
The transition of power systems toward digital substations has brought numerous advantages to substation automation. However, this digital transformation exposes substations to various cyberattacks. Thus, ensuring the integrity and availability of power system data has emerged as a critical concern in modern power system networks. A crucial cybersecurity concern is pilot protection, with its security being of utmost importance in bulk power system networks to safeguard against significant disturbances and blackouts, as well as to facilitate fast fault-clearing operations. This paper introduces a dynamic state estimation (DSE) technique to supervise the operation of pilot protection scheme. The proposed scheme accurately estimates transmission line impedance and uses this estimation to supervise the legacy pilot protection scheme. The method employs network physical laws, sampled value measurements, and an Unscented Kalman Filter (UKF) technique to enhance the cybersecurity aspects of the pilot protection scheme. Additionally, the cybersecurity of the DSE-based pilot protection supervision scheme is evaluated against cyberattacks such as denial of service (DoS) and false data injection (FDI). The simulation results, validated using the IEEE 9 bus test system, demonstrate the effectiveness of the proposed method for pilot protection supervision.
Syed Shafiulla, Manas Kumar Jena
IEEE Trans. Inf. Forensics Secur.1