Name
Title | ||
|---|---|---|
GP^2S: Generic Privacy-Preservation Solutions for Approximate Aggregation of Sensor Data (concise contribution) |
Abstract | ||
|---|---|---|
Protecting privacy in sensor networks poses new challenges because of the potential incompatibilities between new privacy-preserving mechanisms and mechanisms already implemented in sensor networks (such as in-network data aggregation). To address this problem, we propose in this paper a set of new privacy-preservation data aggregation schemes. Different from past research, our solutions have the following features: supporting data aggregation for a variety of queries; providing privacy protection for both individual data and aggregate data; being resilient to any number of node collusion; being highly efficient. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/PERCOM.2008.60 | PerCom |
Keywords | DocType | ISBN |
concise contribution,generic privacy-preservation solutions,data privacy,sensor data,large scale adoption,privacy-preservation data aggregation schemes,approximate sensor data aggregation,wireless sensor networks,telecommunication security,approximate aggregation,mobile computing,adaptive service,reliable privacy-preserving technology,sensor network,data aggregation,intelligent sensors,pervasive computing,collaboration,bandwidth,histograms,computer science,cryptography | Conference | 978-0-7695-3113-7 |
Citations | PageRank | References |
26 | 1.18 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wensheng Zhang | 1 | 1415 | 80.30 |
| Chuang Wang | 2 | 42 | 6.76 |
| Taiming Feng | 3 | 107 | 6.32 |