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Erschienen in: Soft Computing 8/2020

12.07.2019 | Focus

Secure and efficient big data deduplication in fog computing

verfasst von: Jiajun Yan, Xiaoming Wang, Qingqing Gan, Suyu Li, Daxin Huang

Erschienen in: Soft Computing | Ausgabe 8/2020

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Abstract

With the rapid development of the Internet of Things, the massive amount of big data generated by the Internet of Things terminals and the real-time processing requirements have brought enormous challenges. A two-tier computing model consisting solely of two entities, cloud and user, will not be sufficient to support processing large numbers of concurrent data requests. Therefore, fog computing was proposed. How to realize the secure and efficient deduplication of ciphertext in fog computing has become a new research topic. In this paper, we firstly present a new decentralized deduplication structure and then show how to apply it to construct a secure and efficient big data deduplication scheme in fog computing. The cloud server, in the proposed paper, can quickly determine which fog server needs to be traversed to search duplicate data, and instead of traversing all fog servers. This significantly improves the efficiency of big data deduplication in fog computing. Furthermore, the proposed scheme allows fog server to verify whether the user possesses the ownership of the data. Performance analysis and experimental results show the proposed scheme has less overheads than existing schemes.

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Metadaten
Titel
Secure and efficient big data deduplication in fog computing
verfasst von
Jiajun Yan
Xiaoming Wang
Qingqing Gan
Suyu Li
Daxin Huang
Publikationsdatum
12.07.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 8/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-019-04215-9

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