Privacy Preserving OLAP and OLAP Security
نویسندگان
چکیده
منابع مشابه
Theory-Inspired Optimizations for Privacy Preserving Distributed OLAP Algorithms
Actually, a lot of attention focusing on the problem of computing privacy-preserving OLAP cubes effectively and efficiently arises. State-of-theart proposals rather focus on an algorithmic vision of the problem, and neglect relevant theoretical aspects the investigated problem introduces naturally. In order to fulfill this gap, in this paper we provide algorithms for supporting privacy-preservi...
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A constraint-based framework for computing privacy preserving OLAP aggregations on data cubes is proposed and experimentally assessed in this paper. Our framework introduces a novel privacy OLAP notion, which, following consolidated paradigms of OLAP research, looks at the privacy of aggregate patterns defined on multidimensional ranges rather than the privacy of individual tuples/data-cells, l...
متن کاملA Comprehensive Theoretical Framework for Privacy Preserving Distributed OLAP
This paper complements the privacy preserving distributed OLAP framework proposed by us in a previous work by introducing four major theoretical properties that extend models and algorithms presented in the previous work, where the experimental validation of the framework has also been reported. Particularly, our framework makes use of the CUR matrix decomposition technique as the elementary co...
متن کاملPreserving Privacy in On-Line Analytical Processing (OLAP)
A solution to get the problem off, have you found it? Really? What kind of solution do you resolve the problem? From what sources? Well, there are so many questions that we utter every day. No matter how you will get the solution, it will mean better. You can take the reference from some books. And the preserving privacy in on line analytical processing olap is one book that we really recommend...
متن کاملFMC: An Approach for Privacy Preserving OLAP
To preserve private information while providing thorough analysis is one of the significant issues in OLAP systems. One of the challenges in it is to prevent inferring the sensitive value through the more aggregated non-sensitive data. This paper presents a novel algorithm FMC to eliminate the inference problem by hiding additional data besides the sensitive information itself, and proves that ...
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