A compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networks
Toward the goal of high security and efficiency for data collection in wireless sensor network, this article proposed an adaptable secure compressive sensing–based data collection scheme for distributed wireless sensor network. It adopted public key cryptography technology to solve the key distribut...
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1177/1550147719856516 |
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doaj-bc7788ed686d49b98da663e9e656188f2020-11-25T03:03:14ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772019-06-011510.1177/1550147719856516A compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networksZhen LiuYi-Liang HanXiao-Yuan YangToward the goal of high security and efficiency for data collection in wireless sensor network, this article proposed an adaptable secure compressive sensing–based data collection scheme for distributed wireless sensor network. It adopted public key cryptography technology to solve the key distribution problem, and compressive sensing over finite fields to reduce the communication cost of data collection. Under hardness of decisional learning with errors problem on lattice, it can ensure indistinguishability against chosen ciphertext attack (IND-CCA1) security scheme for collected data on the extranet and indistinguishability against chosen plaintext attack security for data during the process of distributed collection on the intranet. Owing to the similar linear structure for lattices and compressive sensing, data encryption collection can be all in the form of efficient linear operations, and internode data aggregation can be in the form of addition operation.https://doi.org/10.1177/1550147719856516 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhen Liu Yi-Liang Han Xiao-Yuan Yang |
spellingShingle |
Zhen Liu Yi-Liang Han Xiao-Yuan Yang A compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networks International Journal of Distributed Sensor Networks |
author_facet |
Zhen Liu Yi-Liang Han Xiao-Yuan Yang |
author_sort |
Zhen Liu |
title |
A compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networks |
title_short |
A compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networks |
title_full |
A compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networks |
title_fullStr |
A compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networks |
title_full_unstemmed |
A compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networks |
title_sort |
compressive sensing–based adaptable secure data collection scheme for distributed wireless sensor networks |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2019-06-01 |
description |
Toward the goal of high security and efficiency for data collection in wireless sensor network, this article proposed an adaptable secure compressive sensing–based data collection scheme for distributed wireless sensor network. It adopted public key cryptography technology to solve the key distribution problem, and compressive sensing over finite fields to reduce the communication cost of data collection. Under hardness of decisional learning with errors problem on lattice, it can ensure indistinguishability against chosen ciphertext attack (IND-CCA1) security scheme for collected data on the extranet and indistinguishability against chosen plaintext attack security for data during the process of distributed collection on the intranet. Owing to the similar linear structure for lattices and compressive sensing, data encryption collection can be all in the form of efficient linear operations, and internode data aggregation can be in the form of addition operation. |
url |
https://doi.org/10.1177/1550147719856516 |
work_keys_str_mv |
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