A Survey on Privacy Preserving Association Rule Mining
نویسندگان
چکیده
منابع مشابه
A Survey on Privacy Preserving Association Rule Mining
Businesses share data, outsourcing for specific business problems. Large companies stake a large part of their business on analysis of private data. Consulting firms often handle sensitive third party data as part of client projects. Organizations face great risks while sharing their data. Most of this sharing takes place with little secrecy. It also increases the legal responsibility of the pa...
متن کاملSurvey on Privacy Preserving Association Rule Data Mining
The progress in the development of data mining techniques achieved in the recent years is gigantic. The collative data mining techniques makes the privacy preserving an important issue. The ultimate aim of the privacy preserving data mining is to extract relevant information from large amount of data base while protecting the sensitive information. The togetherness in the information retrieval ...
متن کاملPrivacy Preserving Association Rule Mining
The current trend in the application space towards systems of loosely coupled and dynamically bound components that enables just-in-time integration jeopardizes the security of information that is shared between the broker, the requester, and the provider at runtime. In particular, new advances in data mining and knowledge discovery, that allow for the extraction of hidden knowledge in enormous...
متن کاملOn a New Scheme on Privacy Preserving Association Rule Mining
We address the privacy preserving association rule mining problem in a system with one data miner and multiple data providers, each holds one transaction. The literature has tacitly assumed that randomization is the only effective approach to preserve privacy in such circumstances. We challenge this assumption by introducing an algebraic techniques based scheme. Compared to previous approaches,...
متن کاملPrivacy Preserving Association Rule Mining Revisited
The privacy preserving data mining (PPDM) has been one of the most interesting, yet challenging, research issues. In the PPDM, we seek to outsource our data for data mining tasks to a third party while maintaining its privacy. In this paper, we revise one of the recent PPDM schemes (i.e., FS) which is designed for privacy preserving association rule mining (PP-ARM). Our analysis shows some limi...
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ژورنال
عنوان ژورنال: International Journal of Data Mining & Knowledge Management Process
سال: 2013
ISSN: 2231-007X,2230-9608
DOI: 10.5121/ijdkp.2013.3208