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Gentz, Reinhard

Publications and source records attributed to Gentz, Reinhard.

Differentially Private K -Means Clustering Applied to Meter Data Analysis and Synthesis

The proliferation of smart meters has resulted in a large amount of data being generated. It is increasingly apparent that methods are required for allowing a variety of stakeholders to leverage the data in a manner that preserves the privacy of the consumers. The sector is scrambling to define policies, such as the so called ‘15/15 rule’, to respond to the need. However, the current policies fail to adequately guarantee privacy. Here, in this paper, we address the problem of allowing third parties to apply K-means clustering, obtaining customer labels and centroids for a set of load time series by applying the framework of differential privacy. We leverage the method to design an algorithm that generates differentially private synthetic load data consistent with the labeled data. We test our algorithm’s utility by answering summary statistics such as average daily load profiles for a 2-dimensional synthetic dataset and a real-world power load dataset.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Supporting Cyber Security of Power Distribution Systems by Detecting Differences Between Real-time Micro-Synchrophasor Measurements and Cyber-Reported SCADA (Final Report)

As modern power grids tend towards greater levels of automation and communication, the challenges of identifying and mitigating vulnerabilities to cyber-attacks are ones that are increasingly demanding attention. Today’s power system has evolved to form the foundational bedrock of modern society, and an attack on this infrastructure could prove disastrous. In this project we were tasked to investigate the use of distribution synchrophasors as an independent isolated sensor network with which we can corroborate, or flag potentially spoofed,Supervisory Control And Data Acquisition (SCADA) data. We adapted an approach to marry the underlying physical properties of power systems with the network communications used by power systems in order to offer insights unattainable by either data stream isolation. While the concept of intrusion detection systems (IDS) is well understood for monitoring network traffic and traditional IT computing systems, the approach discussed in this report is motivated by several key notions: first, current SCADA communications alone presents an incomplete view of the grid. Second, the power grid, and the equipment controlling it, is grounded by laws of physics. Given this, we leverage high-frequency physical grid measurements to understand the physical condition of the grid, and combine this with SCADA. While high-frequency physical grid measurements and SCADA communication over Internet Protocol (IP) networks are fundamentally disparate information sources, when collectively examined through appropriate lenses, they offer a much more nuanced depiction of the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Automated Disruption-Tolerant Key Management Framework for Critical Systems

Key management is critical to secure operation. Distributed control systems, such as Supervisory Control and Data Acquisition (SCADA) systems, have unique operational requirements that make conventional key management solutions less effective and burdensome. This paper presents a novel Kerberos-based framework for automated, disruption-tolerant key management for control system environments. Here, experimental tests and their results are presented to quantify the expected performance overhead of this approach. Additionally, Zeek sensor analytics are presented to aid in monitoring the health and security of the key management framework operation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗