Secure and traceable framework for data circulation

Kaitai Liang, Atsuko Miyaji, Chunhua Su*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

To date the rapid growth of big data processing and its circulation among multiple organizations incur both promising prospects and security challenges for the corresponding technologies, such as data management, data analysis and so on. Efficient and secure data traceability is of critical importance for big data circulation, especially for cloud service applications which are not fully trusted and the risk of leakage of sensitive personal information. In this paper, we propose a framework for mutual traceability for data circulation and secure outsourced computation in data-centric cloud service. Our construction is built on top of searchable attribute-based proxy re-encryption. We enable both data owner and data user to trace their data circulation or perform privacy-preserving feedback. Specifically, the system enables data owners to efficiently distribute and trace his/her data to a specified group of cloud service providers who match a security/privacy policy and meanwhile, the data, maintaining its traceable property, can be further updated after being shared. The new mechanism is applicable to many real-world big data applications. Finally, our framework is proved chosen ciphertext secure in the random oracle model.

Original languageEnglish
Title of host publicationInformation Security and Privacy - 21st Australasian Conference, ACISP 2016, Proceedings
PublisherSpringer Verlag
Pages376-388
Number of pages13
Volume9722
ISBN (Print)9783319402529
DOIs
Publication statusPublished - 2016
MoE publication typeA4 Article in a conference publication
EventAustralasian Conference on Information Security and Privacy - Melbourne, Australia
Duration: 4 Jul 20166 Jul 2016
Conference number: 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9722
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

ConferenceAustralasian Conference on Information Security and Privacy
Abbreviated titleACISP
CountryAustralia
CityMelbourne
Period04/07/201606/07/2016

Keywords

  • Cloud services security
  • Data circulation
  • Data privacy
  • Data traceability

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