Secure and Traceable Framework for Data Circulation
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 sec
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Department of Computer Science, Aalto University, School of Science and Technology, P.O. Box 15400, 00076 Aalto, Finland [email protected] 2 Department of Information and Communications Technology, Graduate School of Engineering, Osaka University, 1-1 Yamadaoka, Suita, Osaka 565-0871, Japan {miyaji,su}@comm.eng.osaka-u.ac.jp 3 Crest, Japan Science and Technology Agency, Honcho, Kawaguchi-shi, Saitama 332-0012, Japan
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 privacypreserving 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. Keywords: Data circulation · Data traceability · Data privacy · Cloud services security
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Introduction
A great amount of companies and research institutes have been using big data technology for the purposes of marketing and research. The circulation of big data among diffident parties that becomes a common form of big data utilization. However, the circulation may bring security and privacy risks for personal sensitive information. From the privacy view point, data owners are usually reluctant c Springer International Publishing Switzerland 2016 J.K. Liu and R. Steinfeld (Eds.): ACISP 2016, Part I, LNCS 9722, pp. 376–388, 2016. DOI: 10.1007/978-3-319-40253-6 23
Secure and Traceable Framework for Data Circulation
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to distribute their data in big data circulation without the aids of security and privacy-enhancing technologies. In this paper, we focus on the security and privacy violation problem during the data circulation (including the data collection and distribution phases), we provide a secure and mutual traceable framework for big data utility among different data owners and cloud service providers. 1.1
Motivation and Problem Statement
Uploading a huge amount of data to remote clouds for big data analysis that helps not only individuals but also companies to make better decision on the next move. Companies, hospitals and research institutions prefer to store c
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