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Revocable Identity-Based Access Control for Big Data with Verifiable Outsourced Computing
School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu.
Department of Information Systems and Cyber Security, The University of Texas at San Antonio.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-1902-9877
2017 (English)In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750Article in journal (Refereed) Epub ahead of print
Abstract [en]

To be able to leverage big data to achieve enhanced strategic insight, process optimization and make informed decision, we need to be an efficient access control mechanism for ensuring end-to-end security of such information asset. Signcryption is one of several promising techniques to simultaneously achieve big data confidentiality and authenticity. However, signcryption suffers from the limitation of not being able to revoke users from a large-scale system efficiently. We put forward, in this paper, the first identity-based (ID-based) signcryption scheme with efficient revocation as well as the feature to outsource unsigncryption to enable secure big data communications between data collectors and data analytical system(s). Our scheme is designed to achieve end-to-end confidentiality, authentication, non-repudiation, and integrity simultaneously, while providing scalable revocation functionality such that the overhead demanded by the private key generator (PKG) in the key-update phase only increases logarithmically based on the cardiality of users. Although in our scheme the majority of the unsigncryption tasks are outsourced to an untrusted cloud server, this approach does not affect the security of the proposed scheme. We then prove the security of our scheme, as well as demonstrating its utility using simulations

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017.
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-64471DOI: 10.1109/TBDATA.2017.2697448OAI: oai:DiVA.org:ltu-64471DiVA: diva2:1114816
Available from: 2017-06-26 Created: 2017-06-26 Last updated: 2017-06-26

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