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Privacy Preserving Mining in Code Profiling Data

Privacy Preserving Mining in Code Profiling Data

apply data mining to d iscover some knowledge so that it will be useful in future development of software. In this work we have applied privacy preserving mining in code profiling data such as software metrics of various codes. Results of data mining on actual and encrypted data are compared for accuracy . We have also analyzed the results of privacy preserving mining in code profiling data ...

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Privacy-Preserving Decision Trees over Vertically ...

Privacy-Preserving Decision Trees over Vertically ...

technique implemented: a demonstration that privacy-preserving distributed data mining is real and usable. The algorithm has been implemented on top of Weka [Witten and Frank 1999], and we present experimental results on sam-ple datasets, showing the times required to build a decision tree and classify instances. While our protocols leak a small amount of extra information (that does not ...

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Privacy Preserving Distributed DBSCAN Clustering

Privacy Preserving Distributed DBSCAN Clustering

The privacy preserving distributed data mining problem in the latter cate-gory is typically formulated as a secure multi-party computation problem [10]. Yao’s general protocol for secure circuit evaluation [26] can be used to solve any two-party privacy preserving distributed data mining problem in theory. However, since data mining problems usually involve millions or billions of data items ...

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Introduction to Privacy Preserving Distributed Data Mining

Introduction to Privacy Preserving Distributed Data Mining

• Efficient/specific cryptographic solutions for many distributed data mining problems are developed. • Mainly semi-honest assumption(i.e. parties follow the protocols)

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Effect of Privacy Protection on Discrimination

Effect of Privacy Protection on Discrimination

discrimination free using privacy preserving model (e.g. t-closeness) is depicted in [14]. The impact of knowledge publishing on anti-discrimination is shown in [15] [16]. Methods for discrimination discovery using privacy attack strategies are presented in [17]. III. BASIC TERMINOLOGIES . A. Basic Definitions in Data Mining . Some basic definitions [3] of data mining are mentioned below ...

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Privacy-Preserving Clustering on Distributed Databases: A ...

Privacy-Preserving Clustering on Distributed Databases: A ...

There is a series of limitations which hinder the utilization of traditional data mining techniques on distributed databases. The approach commonly taken, the gathering of all distributed databases in a central unit, followed by algorithm application, is strongly criticized, because in these cases, it is important to take into consideration some issues, namely: the possibility of existence of ...

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Making Privacy-Preserving Data Mining Practical with ...

Making Privacy-Preserving Data Mining Practical with ...

Data mining provides large bene?ts to the commercial, government and homeland security sectors, but the aggregation and storage of huge amounts of data about citizens inevitably leads to an erosion of privacy. To achieve the bene?ts that data mining has to o?er, while at the same time enhancing privacy, we need technological solutions that simultaneously enable data mining while ...

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Some Requirements for Adoption of Privacy-Preserving Data ...

Some Requirements for Adoption of Privacy-Preserving Data ...

privacy-preserving survey package (built on top of the FairPlay system [MNPS04]) as a solution that would allow them both to provide the requested data and to maintain privacy; and we saw this as an opportunity to pursue the PORTIA research-agenda item of building and experimenting with usable, privacy-preserving data-mining schemes.

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A comprehensive review on privacy preserving data mining

A comprehensive review on privacy preserving data mining

current privacy preserving data mining techniques are classified based on distortion, association rule, hide association rule, taxonomy, clustering, associative classification, outsourced data mining, distributed, and k-anonymity, where their notable advantages and disadvantages are emphasized. This careful scrutiny reveals the past development, present research challenges, future trends, the ...

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Privacy Preserving in Data Mining by Normalization

Privacy Preserving in Data Mining by Normalization

method using min-max normalization for preserving data through data mining. In general, min- max normalization is used as a preprocessing step in data mining for transformation of data to a desired range. Our purpose is to use it for preserving privacy through data mining. We use K- means clustering to validate the proposed approach and validate for accuracy. The rest of the paper is organized ...

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Privacy-Preserving Data Mining - University of Texas at Dallas

Privacy-Preserving Data Mining - University of Texas at Dallas

on privacy-preserving data mining that attempt to maintain privacy and at the same time extract useful information from data mining. Finally, some directions for future research on privacy as related to data mining are given. Keywords: counter-terrorism; data mining; privacy; privacy-preserving data mining; pri-

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