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Scalable and efficient provable data possession

Ateniese, Giuseppe, Di Pietro, Roberto, Mancini, Luigi V., Tsudik, Gene·2008·Proceedings of the 4th international conference on Security and privacy in communication netowrks

Abstract

Storage outsourcing is a rising trend which prompts a number of interesting security issues, many of which have been extensively investigated in the past. However, Provable Data Possession (PDP) is a topic that has only recently appeared in the research literature. The main issue is how to frequently, efficiently and securely verify that a storage server is faithfully storing its client's (potentially very large) outsourced data. The storage server is assumed to be untrusted in terms of both security and reliability. (In other words, it might maliciously or accidentally erase hosted data; it might also relegate it to slow or off-line storage.) The problem is exacerbated by the client being a small computing device with limited resources. Prior work has addressed this problem using either public key cryptography or requiring the client to outsource its data in encrypted form.

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Metadata

Authors
Ateniese, G., Di Pietro, R., Mancini, L. V., & Tsudik, G.
Venue
Proceedings of the 4th international conference on Security and privacy in communication netowrks
Publisher
ACM
Published
2008-09-22
Pages
1-10
OpenAlex
W2040193872
Cited by
1,129
References
0
FWCI
20.72
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Scalable and efficient provable data possession. https://app.cochat.ai/papers/10.1145/1460877.1460889
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Ateniese, G., Di Pietro, R., Mancini, L. V., & Tsudik, G. (2008). Scalable and efficient provable data possession. Proceedings of the 4th international conference on Security and privacy in communication netowrks. https://doi.org/10.1145/1460877.1460889

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.