ArticlePloS one2022
PPTPS: Building privacy-preserving auditable service with traceable timeliness for public cloud storage.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many works are designed to improve efficiency or enhance security and privacy of publicly-auditable cloud storage. However, building timeliness for cloud storage has not been well studied. Few works presented time-sensitive cloud storage and only focused on specific issues, such as the earliest creation time of files or resistance against a procrastinating auditor. Therefore, there leaves an absence of building traceable timeliness for publicly-auditable cloud storage. In this paper, we propose a solution PPTPS to build Privacy-Preserving auditable service with Traceable timeliness for Public cloud Storage. First, we use the security properties of the blockchain to provide a time-stamp for each phase. It enables the timeliness of cloud storage. Second, we construct efficient publicly-verifiable cloud storage. Third, a customized random mask solution is proposed to prevent privacy leakage during the auditing phase. Moreover, we formally proved the security of PPTPS. At last, experimental results demonstrate that PPTPS is economically sound and technically viable.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.