.png){kind=icon}
返回
MSDA: multi-subset data aggregation scheme without trusted third party
.png){kind=icon}
PRE
AI
DOI：10.1007/s11704-021-0316-x.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Data aggregation has been widely researched to address the privacy concern when data is published, meanwhile, data aggregation only obtains the sum or average in an area. In reality, more fine-grained data brings more value for data consumers, such as more accurate management, dynamic price-adjusting in the grid system, etc. In this paper, a multi-subset data aggregation scheme for the smart grid is proposed without a trusted third party, in which the control center collects the number of users in different subsets, and obtains the sum of electricity consumption in each subset, meantime individual user's data privacy is still preserved. In addition, the dynamic and flexible user management mechanism is guaranteed with the secret key negotiation process among users. The analysis shows MSDA not only protects users' privacy to resist various attacks but also achieves more functionality such as multi-subset aggregation, no reliance on any trusted third party, dynamicity. And performance evaluation demonstrates that MSDA is efficient and practical in terms of communication and computation overhead.
Keyword:
multi-subset data aggregation
privacy-preserving
smart gird
dynamic user management
期刊
IF:
4.6
论文数:
1.6K
被引数:
2.8K
机构
引用论文
.png){kind=icon}
分享收藏EPPA: An Efficient and Privacy-Preserving Aggregation Scheme for Secure Smart Grid Communications
OAAI
OAAI分享收藏Highly Efficient Privacy Preserving Location-Based Services with Enhanced One-Round Blind Filter
PREAI
分享收藏Joint Distribution Estimation and Naive Bayes Classification Under Local Differential Privacy局部差分隐私下的联合分布估计和朴素贝叶斯分类
PREAI
分享收藏
查看更多内容