MSDA: multi-subset data aggregation scheme without trusted third party

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Zhixin Zeng ◽  
Xiaodi Wang ◽  
Yining Liu ◽  
Liang Chang
Keyword(s):  
Data Aggregation ◽  
Third Party ◽  
Trusted Third Party ◽  
Aggregation Scheme

scholarly journals Decentralized Privacy-Preserving Data Aggregation Scheme for Smart Grid Based on Blockchain

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5282 ◽  
Author(s):  
Hongbin Fan ◽  
Yining Liu ◽  
Zhixin Zeng
Keyword(s):  
Smart Grid ◽  
Data Aggregation ◽  
Privacy Preserving ◽  
Third Party ◽  
Security And Privacy ◽  
Communication Overhead ◽  
User Privacy ◽  
Grid Data ◽  
Trusted Third Party ◽  
Grid Based

As a next-generation power system, the smart grid can implement fine-grained smart metering data collection to optimize energy utilization. Smart meters face serious security challenges, such as a trusted third party or a trusted authority being attacked, which leads to the disclosure of user privacy. Blockchain provides a viable solution that can use its key technologies to solve this problem. Blockchain is a new type of decentralized protocol that does not require a trusted third party or a central authority. Therefore, this paper proposes a decentralized privacy-preserving data aggregation (DPPDA) scheme for smart grid based on blockchain. In this scheme, the leader election algorithm is used to select a smart meter in the residential area as a mining node to build a block. The node adopts Paillier cryptosystem algorithm to aggregate the user’s power consumption data. Boneh-Lynn-Shacham short signature and SHA-256 function are applied to ensure the confidentiality and integrity of user data, which is convenient for billing and power regulation. The scheme protects user privacy data while achieving decentralization, without relying on TTP or CA. Security analysis shows that our scheme meets the security and privacy requirements of smart grid data aggregation. The experimental results show that this scheme is more efficient than existing competing schemes in terms of computation and communication overhead.

A lightweight and fault-tolerable data aggregation scheme for privacy-friendly smart grids environment

2021 ◽  
Author(s):  
Chengpeng Huang ◽  
Xiaoming Wang ◽  
Qingqing Gan ◽  
Daxin Huang ◽  
Mengting Yao ◽  
...  
Keyword(s):  
Data Aggregation ◽  
Smart Grids ◽  
Aggregation Scheme

Enhancing Privacy in PUF-Cash through Multiple Trusted Third Parties and Reinforcement Learning

2022 ◽  
Vol 18 (1) ◽  
pp. 1-26
Author(s):  
Georgios Fragkos ◽  
Cyrus Minwalla ◽  
Eirini Eleni Tsiropoulou ◽  
Jim Plusquellic
Keyword(s):  
User Anonymity ◽  
Third Party ◽  
Security And Privacy ◽  
Machine Learning Techniques ◽  
User Privacy ◽  
Trusted Third Party ◽  
Physical Unclonable Functions ◽  
Learning Techniques ◽  
Direct Contrast ◽  
Debit Cards

Electronic cash ( e-Cash ) is a digital alternative to physical currency such as coins and bank notes. Suitably constructed, e-Cash has the ability to offer an anonymous offline experience much akin to cash, and in direct contrast to traditional forms of payment such as credit and debit cards. Implementing security and privacy within e-Cash, i.e., preserving user anonymity while preventing counterfeiting, fraud, and double spending, is a non-trivial challenge. In this article, we propose major improvements to an e-Cash protocol, termed PUF-Cash, based on physical unclonable functions ( PUFs ). PUF-Cash was created as an offline-first, secure e-Cash scheme that preserved user anonymity in payments. In addition, PUF-Cash supports remote payments; an improvement over traditional currency. In this work, a novel multi-trusted-third-party exchange scheme is introduced, which is responsible for “blinding” Alice’s e-Cash tokens; a feature at the heart of preserving her anonymity. The exchange operations are governed by machine learning techniques which are uniquely applied to optimize user privacy, while remaining resistant to identity-revealing attacks by adversaries and trusted authorities. Federation of the single trusted third party into multiple entities distributes the workload, thereby improving performance and resiliency within the e-Cash system architecture. Experimental results indicate that improvements to PUF-Cash enhance user privacy and scalability.

scholarly journals An Elliptic Curve-Based Scalable Data Aggregation Scheme for Smart Grid

2020 ◽  
Vol 14 (2) ◽  
pp. 2066-2077
Author(s):  
Yuwen Chen ◽  
Jose-Fernan Martinez-Ortega ◽  
Pedro Castillejo ◽  
Lourdes Lopez
Keyword(s):  
Smart Grid ◽  
Elliptic Curve ◽  
Data Aggregation ◽  
Aggregation Scheme
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