Title
APHID: An architecture for private, high-performance integrated data mining
Abbreviated Journal Title
Futur. Gener. Comp. Syst.
Keywords
Data mining; Privacy; Distributed architectures; PARTITIONED DATA; INFRASTRUCTURE; SERVICES; TOOLKIT; Computer Science, Theory & Methods
Abstract
While the emerging field of privacy preserving data mining (PPDM) will enable many new data mining applications, it suffers from several practical difficulties. PPDM algorithms are challenging to develop and computationally intensive to execute. Developers need convenient abstractions to simplify the engineering of PPDM applications. The individual parties involved in the data mining process need a way to bring high-performance, parallel computers to bear on the computationally intensive parts of the PPDM tasks. This paper discusses APHID (Architecture for Private and High-performance Integrated Data mining), a practical architecture and software framework for developing and executing large scale PPDM applications. At one tier, the system supports simplified use of cluster and grid resources, and at another tier, the system abstracts communication for easy PPDM algorithm development. This paper offers a detailed analysis of the challenges in developing PPDM algorithms with existing frameworks, and motivates the design of a new infrastructure based on these challenges. (C) 2010 Elsevier B.V. All rights reserved.
Journal Title
Future Generation Computer Systems-the International Journal of Grid Computing-Theory Methods and Applications
Volume
26
Issue/Number
7
Publication Date
1-1-2010
Document Type
Article
Language
English
First Page
891
Last Page
904
WOS Identifier
ISSN
0167-739X
Recommended Citation
"APHID: An architecture for private, high-performance integrated data mining" (2010). Faculty Bibliography 2010s. 759.
https://stars.library.ucf.edu/facultybib2010/759
Comments
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