نتایج جستجو برای: privacy preserving
تعداد نتایج: 90476 فیلتر نتایج به سال:
association rules are among important techniques in data mining which are used for extracting hidden patterns and knowledge in large volumes of data. association rules help individuals and organizations take strategic decisions and improve their business processes. extracted association rules from a database contain important and confidential information that if published, the privacy of indivi...
This article first describes the privacy concerns that arise due to data mining, especially for national security applications. Then we discuss privacy-preserving data mining. In particular, we view the privacy problem as a form of inference problem and introduce the notion of privacy constraints. We also describe an approach for privacy constraint processing and discuss its relationship to pri...
This article first describes the privacy concerns that arise due to data mining, especially for national security applications. Then we discuss privacy-preserving data mining. In particular, we view the privacy problem as a form of inference problem and introduce the notion of privacy constraints. We also describe an approach for privacy constraint processing and discuss its relationship to pri...
Recently, privacy preservation has become one of the key issues in data mining. In many data mining applications, computing frequencies of values or tuples of values in a data set is a fundamental operation repeatedly used. Within the context of privacy preserving data mining, several privacy preserving frequency mining solutions have been proposed. These solutions are crucial steps in many pri...
Privacy-preserving data mining techniques could encourage health data custodians to provide accurate information for mining by ensuring that the data mining procedures and results cannot, with any reasonable degree of certainty, violate data privacy. We outline privacypreserving data mining techniques/systems in the literature and in industry. They range from privacy-preserving data publishing,...
As a new computing model, Granular computing provides a new efficient way for solving complicated problems, massive data mining, and fuzzy information processing. Privacy is becoming an increasingly important issue in many data mining applications. In this paper, we combined the existing model of granular computing with personalized privacy-preserving demand, and proposed a new granular computi...
Electronic health record (EHR) system facilitates integrating patients' medical information and improves service productivity. However, user access to patient data in a privacy-preserving manner is still challenging problem. Many studies concerned with security and privacy in EHR systems. Rezaeibagha and Mu [1] have proposed a hybrid architecture for privacy-preserving accessing patient records...
Privacy preserving data mining – getting valid data mining results without learning the underlying data values – has been receiving attention in the research community and beyond. It is unclear what privacy preserving means. This paper provides a framework and metrics for discussing the meaning of privacy preserving data mining, as a foundation for further research in this field.
Privacy preserving is one of the most important research topics in the data security field and it has become a serious concern in the secure transformation of personal data in recent years. For example, different credit card companies and disease control centers may try to build better data sharing or publishing models for privacy protection through privacy preserving data mining techniques (PP...
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