scholarly journals P4G2Go: A Privacy-Preserving Scheme for Roaming Energy Consumers of the Smart Grid-to-Go

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2686
Author(s):  
Aristeidis Farao ◽  
Eleni Veroni ◽  
Christoforos Ntantogian ◽  
Christos Xenakis
Keyword(s):  
Energy Consumption ◽  
Smart Grid ◽  
Privacy Preserving ◽  
Green Economy ◽  
Security And Privacy ◽  
Cryptographic Protocol ◽  
Electricity Bill ◽  
Main Components ◽  
Privacy Issues

Due to its flexibility in terms of charging and billing, the smart grid is an enabler of many innovative energy consumption scenarios. One such example is when a landlord rents their property for a specific period to tenants. Then the electricity bill could be redirected from the landlord’s utility to the tenant’s utility. This novel scenario of the smart grid ecosystem, defined in this paper as Grid-to-Go (G2Go), promotes a green economy and can drive rent reductions. However, it also creates critical privacy issues, since utilities may be able to track the tenant’s activities. This paper presents P4G2Go, a novel privacy-preserving scheme that provides strong security and privacy assertions for roaming consumers against honest but curious entities of the smart grid. At the heart of P4G2Go lies the Idemix cryptographic protocol suite, which utilizes anonymous credentials and provides unlinkability of the consumer activities. Our scheme is complemented by the MASKER protocol, used to protect the consumption readings, and the FIDO2 protocol for strong and passwordless authentication. We have implemented the main components of P4G2Go, to quantitatively assess its performance. Finally, we reason about its security and privacy properties, proving that P4G2Go achieves to fulfill the relevant objectives.

scholarly journals Efficient and Privacy-Preserving Data Aggregation and Dynamic Billing in Smart Grid Metering Networks

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2085 ◽  
Author(s):  
An Braeken ◽  
Pardeep Kumar ◽  
Andrew Martin
Keyword(s):  
Smart Grid ◽  
Data Aggregation ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Smart Meters ◽  
Life Patterns ◽  
Consumption Data ◽  
Secure Data ◽  
Secure Data Aggregation ◽  
Privacy Issues

The smart grid enables convenient data collection between smart meters and operation centers via data concentrators. However, it presents security and privacy issues for the customer. For instance, a malicious data concentrator cannot only use consumption data for malicious purposes but also can reveal life patterns of the customers. Recently, several methods in different groups (e.g., secure data aggregation, etc.) have been proposed to collect the consumption usage in a privacy-preserving manner. Nevertheless, most of the schemes either introduce computational complexities in data aggregation or fail to support privacy-preserving billing against the internal adversaries (e.g., malicious data concentrators). In this paper, we propose an efficient and privacy-preserving data aggregation scheme that supports dynamic billing and provides security against internal adversaries in the smart grid. The proposed scheme actively includes the customer in the registration process, leading to end-to-end secure data aggregation, together with accurate and dynamic billing offering privacy protection. Compared with the related work, the scheme provides a balanced trade-off between security and efficacy (i.e., low communication and computation overhead while providing robust security).

scholarly journals Generating Energy Data for Machine Learning with Recurrent Generative Adversarial Networks

Energies ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 130 ◽  
Author(s):  
Mohammad Navid Fekri ◽  
Ananda Mohon Ghosh ◽  
Katarina Grolinger
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Energy Consumption ◽  
Smart Grid ◽  
Time Series Data ◽  
Security And Privacy ◽  
Series Data ◽  
Generative Adversarial Networks ◽  
Generative Adversarial Network ◽  
Adversarial Networks

The smart grid employs computing and communication technologies to embed intelligence into the power grid and, consequently, make the grid more efficient. Machine learning (ML) has been applied for tasks that are important for smart grid operation including energy consumption and generation forecasting, anomaly detection, and state estimation. These ML solutions commonly require sufficient historical data; however, this data is often not readily available because of reasons such as data collection costs and concerns regarding security and privacy. This paper introduces a recurrent generative adversarial network (R-GAN) for generating realistic energy consumption data by learning from real data. Generativea adversarial networks (GANs) have been mostly used for image tasks (e.g., image generation, super-resolution), but here they are used with time series data. Convolutional neural networks (CNNs) from image GANs are replaced with recurrent neural networks (RNNs) because of RNN’s ability to capture temporal dependencies. To improve training stability and increase quality of generated data, Wasserstein GANs (WGANs) and Metropolis-Hastings GAN (MH-GAN) approaches were applied. The accuracy is further improved by adding features created with ARIMA and Fourier transform. Experiments demonstrate that data generated by R-GAN can be used for training energy forecasting models.

scholarly journals Blockchain in Smart Grids: A Review on Different Use Cases

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4862 ◽  
Author(s):  
Tejasvi Alladi ◽  
Vinay Chamola ◽  
Joel J. P. C. Rodrigues ◽  
Sergei A. Kozlov
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Distribution Systems ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Energy Trading ◽  
Blockchain Technology ◽  
Efficient Data ◽  
Privacy Issues ◽  
The Internet Of Things

With the integration of Wireless Sensor Networks and the Internet of Things, the smart grid is being projected as a solution for the challenges regarding electricity supply in the future. However, security and privacy issues in the consumption and trading of electricity data pose serious challenges in the adoption of the smart grid. To address these challenges, blockchain technology is being researched for applicability in the smart grid. In this paper, important application areas of blockchain in the smart grid are discussed. One use case of each area is discussed in detail, suggesting a suitable blockchain architecture, a sample block structure and the potential blockchain technicalities employed in it. The blockchain can be used for peer-to-peer energy trading, where a credit-based payment scheme can enhance the energy trading process. Efficient data aggregation schemes based on the blockchain technology can be used to overcome the challenges related to privacy and security in the grid. Energy distribution systems can also use blockchain to remotely control energy flow to a particular area by monitoring the usage statistics of that area. Further, blockchain-based frameworks can also help in the diagnosis and maintenance of smart grid equipment. We also discuss several commercial implementations of blockchain in the smart grid. Finally, various challenges to be addressed for integrating these two technologies are discussed.

scholarly journals Challenges and Issues in Cloud Security for WBAN applications - A Systematic Survey

2020 ◽  
pp. 34-47
Author(s):  
Gomathy B ◽  
Ramesh SM ◽  
Shanmugavadivel G
Keyword(s):  
Cloud Security ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Security Model ◽  
Cloud Environment ◽  
Body Area ◽  
Evaluation Strategies ◽  
Security Challenges ◽  
Privacy Issues ◽  
Comprehensive Study

A systematic and comprehensive review of privacy preserving and security challenges in cloud environment is presented in this literature. Since, cloud supports various applications, it requires immediate attention for serious security and privacy issues. Research must focus on efficient security mechanism for cloud-based networks, also it is essential to explore the techniques to maintain the integrity and confidentiality of the data. This paper highlights research challenges and directions concerning the security as a comprehensive study through intensive analysis of various literatures in the last decade, and it is summarized in terms of architecture types, evaluation strategies and security model. We surveyed, investigated and reviewed the articles in every aspect related to security and privacy preserving concepts and identified the following tasks: 1) architecture of wireless body area networks in cloud, 2) security and privacy in cloud based WBAN, 3), Cloud security and privacy issues in cloud 4) diverse authentication and cryptographic approaches, 4) optimization strategies to improve the security performance.

Sign in / Sign up

Export Citation Format

Share Document