PFDAM: Privacy-Preserving Fine-Grained Data Aggregation Scheme Supporting Multifunctionality in Smart Grid

Zhang, Jianhong; Wei, Jie

doi:10.1109/jiot.2024.3356593

IEEE Internet Things J.

2024

DOI: 10.1109/jiot.2024.3356593

|View full text |Cite

PFDAM: Privacy-Preserving Fine-Grained Data Aggregation Scheme Supporting Multifunctionality in Smart Grid

Jianhong Zhang,

Jie Wei

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article4

Relationship

Self Cite0

Independent4

Authors

Journals

Cited by 4 publications

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Lightweight Verifiable Privacy-Preserving Data Aggregation for Smart Grids

Zhu,

Guo,

Abuadbba

et al. 2024

IEEE Internet Things J.

View full text Add to dashboard Cite

Lightweight Verifiable Privacy-Preserving Data Aggregation for Smart Grids

Zhu,

Guo,

Abuadbba

et al. 2024

IEEE Internet Things J.

View full text Add to dashboard Cite

Lightweight verifiable privacy-preserving infectious disease surveillance data aggregation scheme with fault tolerance

YANG,

WEI

et al. 2024

Sci. Sin.-Inf.

View full text Add to dashboard Cite

EADC: An Efficient Anonymous Data Collection Scheme with Blockchain in Internet of Things

Si,

Wang,

Zhao

et al. 2024

Sensors

View full text Add to dashboard Cite

The integration of smart contracts (SCs) within blockchain technology represents a pivotal direction in the evolution of the Internet of Things (IoT), enabling decentralization and enhancing user trust in the system. However, ensuring data privacy is a fundamental challenge that must be addressed during the deployment of these SCs. Many scholars have adopted data aggregation to protect privacy, but these methods are difficult to achieve fine-grained data collection. To this end, this paper proposes an efficient anonymous data collection (EADC) scheme suitable for the IoT environment. The scheme combines matrix algorithms with homomorphic encryption (HE) technology to effectively cut off the connection between users and data during data upload. In addition, the EADC scheme introduces a sophisticated data grouping protocol to improve the overall efficiency of the system. Analysis shows that the scheme can achieve efficient data collection without compromising user privacy.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

PFDAM: Privacy-Preserving Fine-Grained Data Aggregation Scheme Supporting Multifunctionality in Smart Grid

Cited by 4 publications

References 33 publications

Lightweight Verifiable Privacy-Preserving Data Aggregation for Smart Grids

Lightweight Verifiable Privacy-Preserving Data Aggregation for Smart Grids

Lightweight verifiable privacy-preserving infectious disease surveillance data aggregation scheme with fault tolerance

EADC: An Efficient Anonymous Data Collection Scheme with Blockchain in Internet of Things

Contact Info

Product

Resources

About