PIPC: Privacy- and Integrity-Preserving Clustering Analysis for Load Profiling in Smart Grids

Yang, Haomiao; Liang, Shaopeng; Luo, Xizhao; Tang, Dianhua; Li, Hongwei

doi:10.1109/jiot.2021.3125674

Cited by 7 publications

(2 citation statements)

References 35 publications

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“…Note that, unlike other data networks, synchrophasors send their data in plain text without the use of any cryptographic primitives. Therefore, the proposed protocol is exclusively designed for synchrophasor networks for two major reasons: (i) PMUs have limited computational processing power combined with high-intensity traffic makes conventional cryptographic primitives unsuitable [7], and (ii) a critical assumption behind any attack model for synchrophasors is that the adversary is capable of breaking the encryption of PMU packets [8], [9]. Given these two unique characteristics of synchrophasors, the major contributions of this paper are as follows:…”

Section: Introductionmentioning

confidence: 99%

Securing Synchrophasors Using Data Provenance in the Quantum Era

Javed,

Ali Khan,

Ullah

et al. 2024

IEEE Open J. Commun. Soc.

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Trust in the fidelity of synchrophasor measurements is crucial for the correct operation of modern power grids. While most of the existing research on data provenance focuses on the Internet of Things, there is a significant need for effective malicious data detection in power systems. Current methods either fail to detect malicious data modifications or require certain Phasor Measurement Units (PMUs) to be physically secured. To solve these issues, this paper presents a new protocol to establish data provenance in synchrophasor networks. The proposed protocol is based on Physically Unclonable Functions (PUFs) and harnesses the principles of quantum unreality and uncertainty. It aims not only to verify the source of data but also to provide robust protection against data tampering. The proposed protocol serves the purpose of devising new protocols to protect our critical infrastructure sectors in the quantum era. Security and performance analyses, along with experiments conducted on IBM's Qiskit platform, demonstrate that the protocol offers a strong defense against cyberattacks while maintaining a lightweight profile. In particular, the proposed protocol has a worst-case computational complexity of O(1), an execution time per packet bounded by the time required to compute a cryptographically secure hash, and an upper bound for the per packet communication overhead of 256-bits. In terms of storage overhead, the proposed protocol requires each PMU to store the output of a cryptographically secure hash function, while the PDC needs to store one challenge-response pair (CRP) for each PMU.

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Section: Introductionmentioning

confidence: 99%

Securing Synchrophasors Using Data Provenance in the Quantum Era

Javed,

Ali Khan,

Ullah

et al. 2024

IEEE Open J. Commun. Soc.

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“…These technologies encompass industrial data collection and storage, data conversion and transmission, data preprocessing, data visualization, and data analysis [2][3][4]. The IIoT is driving the trend of processing data at the network edges to reduce latency and improve efficiency.…”

Section: Introduction 1backgroundmentioning

confidence: 99%

A Distributed Sensor System Based on Cloud-Edge-End Network for Industrial Internet of Things

Wang

Lin

et al. 2023

Future Internet

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The Industrial Internet of Things (IIoT) refers to the application of the IoT in the industrial field. The development of fifth-generation (5G) communication technology has accelerated the world’s entry into the era of the industrial revolution and has also promoted the overall optimization of the IIoT. In the IIoT environment, challenges such as complex operating conditions and diverse data transmission have become increasingly prominent. Therefore, studying how to collect and process a large amount of real-time data from various devices in a timely, efficient, and reasonable manner is a significant problem. To address these issues, we propose a three-level networking model based on distributed sensor self-networking and cloud server platforms for networking. This model can collect monitoring data for a variety of industrial scenarios that require data collection. It enables the processing and storage of key information in a timely manner, reduces data transmission and storage costs, and improves data transmission reliability and efficiency. Additionally, we have designed a feature fusion network to further enhance the amount of feature information and improve the accuracy of industrial data recognition. The system also includes data preprocessing and data visualization capabilities. Finally, we discuss how to further preprocess and visualize the collected dataset and provide a specific algorithm analysis process using a large manipulator dataset as an example.

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