Deduplication-friendly watermarking for multimedia data in public clouds
Document Type
Conference Proceeding
Publication Date
9-12-2020
Department
Department of Computer Science
Abstract
To store large volumes of cloud data, cloud storage providers (CSPs) use deduplication, by which if data from multiple owners are identical, only one unique copy will be stored. Deduplication can achieve significant storage saving, benefiting both CSPs and data owners. However, for ownership protection, data owners may choose to transform their outsourced multimedia data to “protected formats” (e.g., by watermarking) which disturbs deduplication since identical data may be transformed differently by different data owners. In this work, we initiate research of resolving the fundamental conflict between deduplication and watermarking. We propose DEW, the first secure Deduplication-friEndly Watermarking scheme which neither requires any interaction among data owners beforehand nor requires any trusted third party. Our key idea is to introduce novel protocols which can ensure that identical data possessed by different data owners are watermarked to the same “protected format”. Security analysis and experimental evaluation justify security and practicality of DEW.
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
9783030589509
Recommended Citation
You, W.,
Chen, B.,
Liu, L.,
&
Jing, J.
(2020).
Deduplication-friendly watermarking for multimedia data in public clouds.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),
12308 LNCS, 67-87.
http://doi.org/10.1007/978-3-030-58951-6_4
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/14502
Publisher's Statement
© Springer Nature Switzerland AG 2020. Publisher’s version of record: https://doi.org/10.1007/978-3-030-58951-6_4