Building an Authentication and Quality of Query Services in the Cloud

AbstractCloud outpouring is careful when an information distributor has given sensitive data to a set of trusted agents and few o f the information is leaked and found in an unauthorized place. An enterprise data leak may be a scary proposition. Security practitioners always deal with data cloud leakage issues that arise from various ways like e-mail and different net channels. In case of information cloud leakage from trusted agents, the distributor should assess the probability that the leaked information came from one or more agents.The proposed system can identify those parties who are guilty for such cloud leakage even once the data is altered. For this the system will use data allocation ways are also can inject “realistic but fake” information records improve the identification of cloud leakage. Moreover, data can also be leaked from inside an organization through e-mail. Hence there's also a need to filter these e-mails, may be done by blocking e-mails that contain pictures, videos or sensitive data in an organization. A principle utilized in e-mail filtering is classify e-mail based mostly the fingerprints of message bodies, the white and black lists of mail addresses and the words specified to spam

A novel verification of trustiness and authentication of query answers in cloud

Propose a helpful question answer confirmation plot which applies to cloud. This plan can not just check the trustiness, culmination, legitimacy of the inquiry answers productively, yet in addition fulfill DO's prerequisite for namelessness and assurance non-revocation benefit among CSP and client. Initially, the proposed plan picks and signs the KN in the MHT dependent on the ring mark conspire, which can both confirm the right of inquiry result when keeping DO mysterious, and underpins various DOs. Also, we present a non-disavowal convention dependent on VO to unravel the repudiable practices of CSP and client

Efficient verification of trustiness and authentication of query answers in cloud

This recommends a cooperative query answer authentication system, based on the ring signature, the Merkle hash tree (MHT) and the non-repudiable service protocol. Through the cooperation among the entities in cloud service system, the proposed scheme could not only verify the query answer but also protect the DO’s identity. First, it picks up the internal nodes of MHT to sign, as well as the root node. Thus, the verification computation complexity could be significantly reduced from O(log2N) to O(log2N0.5) in the best case. Then it improves an existing ring signature to sign the selected nodes. Furthermore, the proposed scheme employs the non-repudiation protocol during the transmission of query answer and verification object (VO) to protect trading behavior between the CSP and users. The security and performance analysis prove the security and feasibility of the proposed scheme

Building Confidential and Efficient Query Services in the Cloud with RASP Data Perturbation

With the wide deployment of public cloud computing infrastructures, using clouds to host data query services has become an appealing solution for the advantages on scalability and cost-saving. However, some data might be sensitive that the data owner does not want to move to the cloud unless the data confidentiality and query privacy are guaranteed. On the other hand, a secured query service should still provide efficient query processing and significantly reduce the in-house workload to fully realize the benefits of cloud computing. We propose the RASP data perturbation method to provide secure and efficient range query and kNN query services for protected data in the cloud. The RASP data perturbation method combines order preserving encryption, dimensionality expansion, random noise injection, and random projection, to provide strong resilience to attacks on the perturbed data and queries. It also preserves multidimensional ranges, which allows existing indexing techniques to be applied to speedup range query processing. The kNN-R algorithm is designed to work with the RASP range query algorithm to process the kNN queries. We have carefully analyzed the attacks on data and queries under a precisely defined threat model and realistic security assumptions. Extensive experiments have been conducted to show the advantages of this approach on efficiency and security.Comment: 18 pages, to appear in IEEE TKDE, accepted in December 201