Brief announcement: Towards security and privacy for outsourced data in the multi-party setting

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Maffei M, Malavolta G, Reinert M, Schröder D, Malavolta G
Publisher: Association for Computing Machinery
Publication year: 2014
Pages range: 144-146
ISBN: 9781450329446
Language: English


Abstract


Cloud storage has rapidly acquired popularity among users, constituting a seamless solution for the backup, synchronization, and sharing of large amounts of data. This technology, however, puts user data in the direct control of cloud service providers, which raises increasing security and privacy concerns related to the integrity of outsourced data, the accidental or intentional leakage of sensitive information, the profiling of user activities and so on. We present GORAM, a cryptographic system that protects the secrecy and integrity of the data outsourced to an untrusted server and guarantees the anonymity and unlinkability of consecutive accesses to such data. GORAM allows the database owner to share outsourced data with other clients, selectively granting them read and write permissions. GORAM is the first system to achieve such a wide range of security and privacy properties for outsourced storage. Technically, GORAM builds on a combination of ORAM to conceal data accesses, attribute-based encryption to rule the access to outsourced data, and zero-knowledge proofs to prove read and write permissions in a privacy-preserving manner. We implemented GORAM and conducted an experimental evaluation to demonstrate its feasibility.



FAU Authors / FAU Editors

Malavolta, Giulio
Lehrstuhl für Informatik 13 (Angewandte Kryptographie)
Schröder, Dominique Prof. Dr.
Lehrstuhl für Informatik 13 (Angewandte Kryptographie)


External institutions
Universität des Saarlandes (UdS)


How to cite

APA:
Maffei, M., Malavolta, G., Reinert, M., Schröder, D., & Malavolta, G. (2014). Brief announcement: Towards security and privacy for outsourced data in the multi-party setting. (pp. 144-146). Paris: Association for Computing Machinery.

MLA:
Maffei, Matteo, et al. "Brief announcement: Towards security and privacy for outsourced data in the multi-party setting." Proceedings of the 2014 ACM Symposium on Principles of Distributed Computing, PODC 2014, Paris Association for Computing Machinery, 2014. 144-146.

BibTeX: 

Last updated on 2018-03-12 at 13:50