Visible to the public Provenance-based Classification Policy based on Encrypted Search

TitleProvenance-based Classification Policy based on Encrypted Search
Publication TypeConference Paper
Year of Publication2020
AuthorsFan, X., Zhang, F., Turamat, E., Tong, C., Wu, J. H., Wang, K.
Conference Name2020 2nd International Conference on Industrial Artificial Intelligence (IAI)
Date Publishedoct
KeywordsAccess Control, Adaptation models, authorisation, cloud computing, cloud data, cloud document classification, cloud storage, compositionality, cryptography, data integrity, data quality, digital provenance, digital signatures, document category, document handling, encrypted provenance, Encrypted Search, Encryption, encryption audits, Games, information retrieval, integrity data, keyword searching, Offline Guessing Attack, pattern classification, Predictive Metrics, Privacy Third Party Auditing, provenance-based classification policy, pubcrawl, Public key, Resiliency, security, security protection, semantic security, sensitive information, storage management
AbstractAs an important type of cloud data, digital provenance is arousing increasing attention on improving system performance. Currently, provenance has been employed to provide cues regarding access control and to estimate data quality. However, provenance itself might also be sensitive information. Therefore, provenance might be encrypted and stored in the Cloud. In this paper, we provide a mechanism to classify cloud documents by searching specific keywords from their encrypted provenance, and we prove our scheme achieves semantic security. In term of application of the proposed techniques, considering that files are classified to store separately in the cloud, in order to facilitate the regulation and security protection for the files, the classification policies can use provenance as conditions to determine the category of a document. Such as the easiest sample policy goes like: the documents have been reviewed twice can be classified as “public accessible”, which can be accessed by the public.
DOI10.1109/IAI50351.2020.9262173
Citation Keyfan_provenance-based_2020