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Cluster Computing
Erschienen in: Cluster Computing 2/2017

20.04.2017

A fine-grained and lightweight data access control scheme for WSN-integrated cloud computing

verfasst von: Heng He, Ji Zhang, Jinguang Gu, Yan Hu, Fangfang Xu

Erschienen in: Cluster Computing | Ausgabe 2/2017

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Abstract

WSN-integrated cloud computing (WCC) has become a promising cloud service architecture, in which sensors and mobile devices are utilized as the data collecting and processing nodes for the cloud service model, while cloud servers can provide computing services and storage services with high performance and reliability. However, since cloud servers are not fully trusted, and sensors and mobile devices have very limited computing capability and storage capacity, WCC brings forth new challenges for data confidentiality, data integrity and access control when sensors store important data for sharing in the WCC environment. Moreover, there are still no proper solutions for fine-grained, efficient and secure data access control in WCC. To solve this issue, we propose a fine-grained and lightweight data access control scheme for WCC, namely FLAC, which includes a ciphertext-policy attribute-based encryption algorithm for data confidentiality and fine-grained data access control, and an attribute-based signature algorithm for data integrity and the many-read-many-write case of data access. By delegating most computation intensive tasks to cloud services, FLAC enables resource constrained sensors and mobile devices to perform security operations rapidly. The security assessment and performance evaluation demonstrate that FLAC is secure, highly efficient and well suited for WSN applications.
Vorheriger Artikel A new canonical polyadic decomposition algorithm with improved stability and its applications to biomedical signal processing
Nächster Artikel Predicting edge sign and finding prestige of nodes in networks

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Metadaten
Titel
A fine-grained and lightweight data access control scheme for WSN-integrated cloud computing
verfasst von
Heng He
Ji Zhang
Jinguang Gu
Yan Hu
Fangfang Xu
Publikationsdatum
20.04.2017
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 2/2017
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-0863-y

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