To protect data privacy and combat unsolicited accesses in the cloud and beyond, sensitive data, e.g., emails, personal health records, photo albums, tax documents, financial transactions, etc., may have to be encrypted by data owners before outsourcing to the commercial public cloud; this, however, obsoletes the traditional data utilization service based on plaintext keyword search. […]
SPARSE REPRESENTATION BASED FINGERPRINT COMPRESSION
Large volumes of fingerprint are collected and stored every day in a wide range of applications, including forensics and access control. Due to the large number and size of fingerprint images, data compression has to be applied to reduce the storage and communication bandwidth requirements of those images. Obtaining an over complete dictionary from a […]
AN EFFICIENT MULTI-KEYWORD RANKED SEARCH SCHEME OVER ENCRYPTED CLOUD DATA
In this abstract, for the first time, we define and solve the problem of multi-keyword ranked search over encrypted cloud data (MRSE) while preserving strict system-wise privacy in the cloud computing paradigm. Among various multi-keyword semantics, we choose the efficient similarity measure of “coordinate matching”, i.e., as many matches as possible, to capture the relevance […]
A NOVEL PUBLIC AUDITING MECHANISM FOR THE INTEGRITY OF SHARED DATA WITH EFFICIENT USER REVOCATION IN THE CLOUD
In this abstract, we propose Panda, a novel public auditing mechanism for the integrity of shared data with efficient user revocation in t he cloud. In our mechanism, by utilizing the idea of proxy re-signatures, once a user in the group is revoked, the cloud is able to re-sign the blocks, which were signed by […]
PUBLIC AUDITING FOR SHARED DATA WITH USER REVOCATION IN THE CLOUD USING PANDA
Cloud providers promise a more secure and reliable environment to the users, the integrity of data in the cloud may still be compromised, due to the existence of hardware/ software failures and human errors. An important problem we need to consider is that the re- computation of any signature during user revocation should not affect […]
A NOVEL FINGERPRINT COMPRESSION ALGORITHM BASED ON SPARSE REPRESENTATION
A new compression algorithm adapted to fingerprint images is introduced. Despite the simplicity of our proposed algorithms, they compare favorably with existing more sophisticated algorithms, especially at high compression ratios. Due to the block-by-block processing mechanism, however, the algorithm has higher complexities. The proposed method has the ability by updating the dictionary. The specific process […]
ANONYMITY BASED ACCURACY-CONSTRAINED PRIVACY-PRESERVING ACCESS CONTROL FRAMEWORK FOR RELATIONAL DATA
In this abstract the focus is on a static relational table that is anonymized only once. To exemplify our approach, role-based access control is assumed. However, the concept of accuracy constraints for permissions can be applied to any privacy-preserving security policy, e.g., discretionary access control. The heuristics proposed in this abstract for accuracy-constrained privacy-preserving access […]
RELATIONAL DATA WITH ACCURACY-CONSTRAINED PRIVACY-PRESERVING ACCESS CONTROL FRAMEWORK
The concept of privacy-preservation for sensitive data can require the enforcement of privacy policies or the protection against identity disclosure by satisfying some privacy requirements. In this abstract, we investigate privacy-preservation from the anonymity aspect. The sensitive information, even after the removal of identifying attributes, is still susceptible to linking attacks by the authorized users. […]
A NOVEL CONSENSUS-BASED RANKING METHOD FOR THE PROBLEM OF TOP-K QUERY ON MULTIVALUED OBJECTS
A novel consensus-based ranking method, named BC ranking, is proposed for the problem of top k query on multivalued objects. The Effective and efficient algorithms are developed to compute the top k query based on BC ranks. The Effective pruning techniques are proposed to significantly improve the performance in terms of CPU and I/O costs. […]
EFFECTIVE AND EFFICIENT BORDA COUNT APPROACH USING INDEX BASED ALGORITHM FOR TOP-K QUERY ON MULTIVALUED OBJECTS
As ranking is an essential analytic method, it is natural and fundamental to investigate how to rank a set of multivalued objects. To the best of our knowledge, however, there is no existing work addressing this important problem systematically. One may think we may simply rank multivalued objects as uncertain/probabilistic data. However, the models of […]
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