Co-Simulation Framework For Network Attack Generation and Monitoring
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24 POWER TRANSMISSION AND DISTRIBUTION↗
Engineering topics
Niddodi, Shwetha
Publications and source records attributed to Niddodi, Shwetha.
Leveraging High-Fidelity Datasets for Machine Learning-based Anomaly Detection in Smart Grids
Data-driven intrusion detection systems are increasingly becoming essential for protecting critical cyber-physical infrastructure, such as the power grid, against the growing number of sophisticated cyber-attacks. The development of such tools is reliant on the availability of high-fidelity cyber-physical datasets that cover a diverse variety of potential cyber events. In this work, a high-fidelity smart grid platform is utilized to develop an extensive dataset, which is used to train and test a machine learning-based intrusion detection system. The evaluation of the developed IDS shows robust performance even when tested with statistically diverse test data not used in training.
Hyder, Burhan↗
pnnl/ssass-e
SSASSE software is responsible for validating, and verifying innovative safe scanning methodologies, models, architectures, and prototypes to safely assess operational technology (OT) installed in critical energy infrastructure.
Niddodi, Shwetha↗