Blockchain-based anomaly detection of electricity consumption in smart grids

Every day, large-scale data are continuously generated on social media as streams, such as Twitter, which inform us about all events around the world in real-time. Notably, Twitter is one of the effective platforms to update countries leaders and scientists during the coronavirus (COVID-19) pandemic. Other people have also used this platform to post their concerns about the spread of this virus and a rapid increase of death cases globally. The aim of this work is to detect anomalous events associated with COVID-19 from Twitter. To this end, we propose a distributed Directed Acyclic Graph topology framework to aggregate and process large-scale real-time tweets related to COVID-19. The core of our system is a novel lightweight algorithm that can automatically detect anomaly events. In addition, our system can also identify, cluster, and visualize important keywords in tweets. On 18 August 2020, our model detected the highest anomaly since many tweets mentioned the casualties’ updates and the debates on the pandemic that day. We obtained the three most commonly listed terms on Twitter: “covid”, “death”, and “Trump” (21566, 11779, and 4761 occurrences, respectively), with the highest TF-IDF score for these terms: “people” (0.63637), “school” (0.5921407) and “virus” (0.57385). From our clustering result, the word “death”, “corona”, and “case” are grouped into one cluster, where the word “pandemic”, “school”, and “president” are grouped as another cluster. These terms were located near each other on vector space so that they were clustered, indicating people’s most concerned topics on Twitter.

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“…Meng Li et al. in [11] proposed a k-Nearest Neighbour algorithm implementation to detect anomaly using blockchain and sensor networks.…”

Section: Related Workmentioning

confidence: 99%

Big data directed acyclic graph model for real-time COVID-19 twitter stream detection

Amen

Faiz²,

Toan

2022

Pattern Recognition

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“…Apart from smart grid data management some of the other big data platforms developed include: In [30], 'SealedGRID' a highly trusted and interoperable smart grid security platform has been presented which abides the blockchain concept with the web of trust. An anamoly detection framework has also been proposed based on big data and machine learning using the blockcahin technology [31]. In [32] 'UlTraMan a unified platform for big data management and analytics for trajectory data is proposed.…”

Section: ) Cidap -Big Data Platform For Smart Citiesmentioning

confidence: 99%

Big Data Management in Smart Grids: Technologies and Challenges

et al. 2021

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Smart grids are re-engineering the electricity transmission and distribution system throughout the world. It is an amalgam of increased digital information with the electrical power grids. Managing the data generated from the grid efficiently is the key to successful knowledge extraction from the smart grid big data. Most of the scientific advancements are becoming data-driven and becoming an interesting area of research for data scientists. It is challenging the world computationally enough to develop new storage methods and data processing technologies. Managing big data involves data cleaning, integration of varied data sources, and decision-making applications. This paper focuses on the study of big data management and proposes a management process to help manage the data in the grid. Data management tools and techniques have been leveraged in understanding the sources and data types in the grid. The paper emphasizes the limitations of the existing solutions inclined towards applications of the smart grid big data.

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“…Li et al [20] mentioned a blockchain-based method for detecting abnormal electricity consumption in smart grids, aiming to use sensor processing, smart meter readings, machine learning, and blockchain to accurately and timely detect electricity consumption abnormality.…”

Section: Smart Grid Combined With Blockchain-related Workmentioning

confidence: 99%

Smart Grid Nontechnical Loss Detection Based on Power Gateway Consortium Blockchain

Wang

Liu

et al. 2021

Security and Communication Networks

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The rapid development of the smart grid brings convenience to human beings. It enables users to know the real-time power supply capacity, the power quality, and the electricity price fluctuation of the grid. However, there are still some threats in the smart grid, which increase all kinds of expenses in the grid and cause great trouble to energy distribution. Among them, the man-made nontechnical loss (NTL) problem is particularly prominent. Recently, there are also some NTL detection programs. However, most of the schemes need huge amounts of supporting data and high labor costs. As a result, the NTL problem has not been well solved. In order to better avoid these risks, problems such as tampering of smart meter energy data, bypassing the smart meter directly connected to the grid, and imbalance between revenue and expenditure of the smart grid are tackled, and the threat scene of NTL is constructed. A hierarchical grid gateway blockchain is proposed and designed, and a new decentralized management MDMS system is constructed. The intelligent contract combined with the elliptic curve encryption technology is used to detect the storage and the acquisition of power data, and the detection of NTL problems is realized. At the same time, it has a certain ability to resist attacks such as replay, monitoring, and tampering. We tested the time consumption and throughput of this method on Hyperledger Fabric. At the same time, eight indexes of other methods proposed in the literature are compared. This method has a good effect.

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Blockchain-based anomaly detection of electricity consumption in smart grids

Cited by 50 publications

References 15 publications

Big data directed acyclic graph model for real-time COVID-19 twitter stream detection

Big data directed acyclic graph model for real-time COVID-19 twitter stream detection

Big Data Management in Smart Grids: Technologies and Challenges

Smart Grid Nontechnical Loss Detection Based on Power Gateway Consortium Blockchain

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