Achieving private, scalable, and precise data collection in wireless sensor networks

Wireless Sensor Networks (WSN) become increasingly popular to collect data over a large area. Given the collected data set, the network manager can extract various kinds of aggregate statistics from the set to characterize the physical space. On the collection of the data, three requirements should...

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Main Authors: Qi, Saiyu., Li, Zhenjiang., Liu, Yunhao.
Other Authors: School of Computer Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/98029
http://hdl.handle.net/10220/12388
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-980292020-05-28T07:17:16Z Achieving private, scalable, and precise data collection in wireless sensor networks Qi, Saiyu. Li, Zhenjiang. Liu, Yunhao. School of Computer Engineering IEEE International Conference on Parallel and Distributed Systems (18th : 2012 : Singapore) DRNTU::Engineering::Computer science and engineering Wireless Sensor Networks (WSN) become increasingly popular to collect data over a large area. Given the collected data set, the network manager can extract various kinds of aggregate statistics from the set to characterize the physical space. On the collection of the data, three requirements should be imposed: (1) Privacy: as sensor nodes are source limited and often deployed in an open environment, the sensed data suffer from privacy vulnerabilities. Secure mechanism should be provided to protect data privacy, (2) Communication efficiency: collecting data from large-scale sensor networks often involves large-volume data generation and transmission, which may quickly consume the energy of the WSN. To prolong the lifetimes of the sensor nodes, the sensed data should be transmitted in lightweight manner, (3) Accuracy: the sensed data should be recovered accurately at the base station (BS) so that the manager can manipulate them freely to achieve any precise aggregate statistic he prefers. To satisfy these requirements, we propose two novel privacy-preserving data collection schemes based on compressive sensing techniques. Our schemes address the privacy, communication efficiency and accuracy issues simultaneously. Detailed theoretical analysis and simulation results confirm the high performance of the proposed schemes. 2013-07-26T06:28:55Z 2019-12-06T19:49:50Z 2013-07-26T06:28:55Z 2019-12-06T19:49:50Z 2012 2012 Conference Paper Qi, S., Li, Z., & Liu, Y. (2012). Achieving private, scalable, and precise data collection in Wireless Sensor Networks. 2012 IEEE 18th International Conference on Parallel and Distributed Systems(ICPADS). https://hdl.handle.net/10356/98029 http://hdl.handle.net/10220/12388 10.1109/ICPADS.2012.13 en © 2012 IEEE.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Qi, Saiyu.
Li, Zhenjiang.
Liu, Yunhao.
Achieving private, scalable, and precise data collection in wireless sensor networks
description Wireless Sensor Networks (WSN) become increasingly popular to collect data over a large area. Given the collected data set, the network manager can extract various kinds of aggregate statistics from the set to characterize the physical space. On the collection of the data, three requirements should be imposed: (1) Privacy: as sensor nodes are source limited and often deployed in an open environment, the sensed data suffer from privacy vulnerabilities. Secure mechanism should be provided to protect data privacy, (2) Communication efficiency: collecting data from large-scale sensor networks often involves large-volume data generation and transmission, which may quickly consume the energy of the WSN. To prolong the lifetimes of the sensor nodes, the sensed data should be transmitted in lightweight manner, (3) Accuracy: the sensed data should be recovered accurately at the base station (BS) so that the manager can manipulate them freely to achieve any precise aggregate statistic he prefers. To satisfy these requirements, we propose two novel privacy-preserving data collection schemes based on compressive sensing techniques. Our schemes address the privacy, communication efficiency and accuracy issues simultaneously. Detailed theoretical analysis and simulation results confirm the high performance of the proposed schemes.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Qi, Saiyu.
Li, Zhenjiang.
Liu, Yunhao.
format Conference or Workshop Item
author Qi, Saiyu.
Li, Zhenjiang.
Liu, Yunhao.
author_sort Qi, Saiyu.
title Achieving private, scalable, and precise data collection in wireless sensor networks
title_short Achieving private, scalable, and precise data collection in wireless sensor networks
title_full Achieving private, scalable, and precise data collection in wireless sensor networks
title_fullStr Achieving private, scalable, and precise data collection in wireless sensor networks
title_full_unstemmed Achieving private, scalable, and precise data collection in wireless sensor networks
title_sort achieving private, scalable, and precise data collection in wireless sensor networks
publishDate 2013
url https://hdl.handle.net/10356/98029
http://hdl.handle.net/10220/12388
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