Introduction to the special section on Security and Privacy Issues in Smart Grid by Applying Deep Learning Techniques (VSI-gridl)

2021 ◽  
Vol 93 ◽  
pp. 107331
Author(s):  
Gwanggil Jeon ◽  
Abdellah Chehri
Keyword(s):  
Deep Learning ◽  
Smart Grid ◽  
Special Section ◽  
Security And Privacy ◽  
Learning Techniques ◽  
Privacy Issues

Deep Learning Techniques for IoT Security and Privacy

2022 ◽  
Author(s):  
Mohamed Abdel-Basset ◽  
Nour Moustafa ◽  
Hossam Hawash ◽  
Weiping Ding
Keyword(s):  
Deep Learning ◽  
Security And Privacy ◽  
Iot Security ◽  
Learning Techniques

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 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.

Security and Privacy Issues in Deep Learning: A Brief Review

2020 ◽  
Vol 1 (5) ◽  
Author(s):  
Trung Ha ◽  
Tran Khanh Dang ◽  
Hieu Le ◽  
Tuan Anh Truong
Keyword(s):  
Deep Learning ◽  
Security And Privacy ◽  
Privacy Issues

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 Efficient and Privacy-Aware Power Injection over AMI and Smart Grid Slice in Future 5G Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yinghui Zhang ◽  
Jiangfan Zhao ◽  
Dong Zheng
Keyword(s):  
Smart Grid ◽  
Security And Privacy ◽  
5G Networks ◽  
User Privacy ◽  
Storage Unit ◽  
Utility Company ◽  
Power Injection ◽  
Aggregation Technique ◽  
Advanced Metering ◽  
Privacy Issues

Smart grid is critical to the success of next generation of power grid, which is expected to be characterized by efficiency, cleanliness, security, and privacy. In this paper, aiming to tackle the security and privacy issues of power injection, we propose an efficient and privacy-aware power injection (EPPI) scheme suitable for advanced metering infrastructure and 5G smart grid network slice. In EPPI, each power storage unit first blinds its power injection bid and then gives the blinded bid together with a signature to the local gateway. The gateway removes a partial blind factor from each blinded bid and then sends to the utility company aggregated bid and signature by using a novel aggregation technique called hash-then-addition. The utility company can get the total amount of collected power at each time slot by removing a blind factor from the aggregated bid. Throughout the EPPI system, both the gateway and the utility company cannot know individual bids and hence user privacy is preserved. In particular, EPPI allows the utility company to check the integrity and authenticity of the collected data. Finally, extensive evaluations indicate that EPPI is secure and privacy-aware and it is efficient in terms of computation and communication cost.

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