In this abstract, we analyze the characteristics of difficult queries over databases and propose a novel method to detect such queries. We propose the Structured Robustness (SR) score, which measures the difficulty of a query based on the differences between the rankings of the same query over the original and noisy (corrupted) versions of the […]
A SECUREDBAAS ARCHITECTURE FOR DISTRIBUTED, CONCURRENT, AND INDEPENDENT ACCESS TO ENCRYPTED CLOUD DATABASES
In this abstract proposed a novel SecureDBaaS architecture that integrates cloud database services with data confidentiality and the possibility of executing concurrent operations on encrypted data. It guarantees data confidentiality by allowing a cloud database server to execute concurrent SQL operations (not only read/write, but also modifications to the database structure) over encrypted data. It […]
CAPACITY SHARING STRATEGY IN A FEDERATION OF SELFISH CLOUD PROVIDERS
Federated clouds approach the CP problem by allowing peer CPs to share their unused capacities during low-demand periods and borrow spare capacity during peaks to maximize their profits and enhance their clients’ experience, with several strategies for capacity sharing in the federation. The proposed work models the interactions among the CPs as a repeated game […]
MULTIVARIATE CORRELATION ANALYSIS BASED DOS ATTACK DETECTION
A denial of service (DoS) attack is a malicious attempt to make a server or a network resource unavailable to users, usually by temporarily interrupting or suspending the services of a host connected to the Internet. They impose intensive computation tasks to the victim by exploiting its system vulnerability or flooding it with huge amount […]
SECURE TWO-PARTY DIFFERENTIALLY PRIVATE DATA RELEASE IN THE SEMIHONEST ADVERSARY MODEL FOR VERTICALLY PARTITIONED DATA
In this abstract, we propose an algorithm to securely integrate person-specific sensitive data from two data providers, whereby the integrated data still retain the essential information for supporting data mining tasks. Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among the existing privacy models, differential privacy provides one […]
PACK: A NOVEL TRE TECHNIQUE BASED CLOUD BANDWIDTH AND COST REDUCTION SYSTEM
Many cloud customers, applying a judicious use of the cloud’s resources, are motivated to use various traffic reduction techniques, in particular traffic redundancy elimination (TRE), for reducing bandwidth costs. TRE is used to eliminate the transmission of redundant content and, there-fore, to significantly reduce the network cost. In this paper, we present PACK (Predictive ACKs), […]
AGGREGATE FUNCTION AND BITMAP INDEX-BASED SET PREDICATES IN SQL FOR DYNAMICALLY FORMED GROUPS
Data warehousing and OLAP applications becoming more sophisticated, there is a high demand of querying data with the semantics of set-level comparisons. The proposed concise syntax of set predicates enables direct expression of set-level comparisons in SQL, which not only makes query formulation simple but also facilitates efficient support of such queries. In data warehousing […]
CP-ABE BASED SECURE DATA RETRIEVAL SCHEME FOR DECENTRALIZED DISRUPTION-TOLERANT MILITARY NETWORKS
Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptographic solution to the access control issues. Ciphertext-policy ABE provides a scalable way of encrypting data such that the encryptor defines the attribute set that the decryptor needs to possess in order to de-crypt the ciphertext. Thus, different users are allowed to decrypt different pieces of data per […]
DIFFERENTIALLY PRIVATE DATA RELEASE FOR VERTICALLY PARTITIONED DATA BETWEEN TWO PARTIES
In this abstract, we present an algorithm for differentially private data release for vertically partitioned data between two parties. Additionally, the proposed algorithm satisfies the security definition of the semi honest adversary model. In this model, parties follow the algorithm but may try to deduce additional information from the received messages. Therefore, at any time […]
BACK-PROPAGATION NEURAL NETWORK LEARNING ALGORITHM FOR PRIVACY PRESERVING IN CLOUD COMPUTING
Back -Propagation is an effective method for learning neural networks and has been widely used in various applications. The accuracy of the learning result, despite other facts, is highly affected by the volume of high-quality data used for learning. As compared to learning with only local data set, collaborative learning improves the learning accuracy by […]
- « Previous Page
- 1
- …
- 10
- 11
- 12
- 13
- 14
- …
- 17
- Next Page »