Secure and traceable framework for data circulation

Kaitai Liang, Atsuko Miyaji, Chunhua Su*

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


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
EditorsJoseph K. Liu, Ron Steinfeld
Number of pages13
ISBN (Print)9783319402529
Publication statusPublished - 1 Jan 2016
Externally publishedYes
Event21st Australasian Conference on Information Security and Privacy, ACISP 2016 - Melbourne, Australia
Duration: 4 Jul 20166 Jul 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference21st Australasian Conference on Information Security and Privacy, ACISP 2016


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


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