We propose a protocol for secure mining of association rules in horizontally distributed databases. The current leading protocol is that of Distribute Database Algorithm. Our protocol, like theirs, is based on the Fast Distributed Mining (FDM) algorithm. Which is an unsecured distributed version of the Apriority algorithm? The main ingredients in our protocol are two novel secure multi-party algorithms — one that computes the union of a private subsets that each of the interacting players holds, and another that tests the inclusion of an element held by one player in a separation held by another. Our protocol offers enhanced privacy concerning the protocol. Also it is simpler and is significantly more efficient regarding communicat...
Data mining is the Data mining is the analysis step of the "Knowledge Discovery in Databases" proces...
With the existence of many large transaction databases, the huge amounts of data, the high scalabili...
Abstract — Data mining can extract important knowledge from large data collections – but sometimes t...
Abstract—We propose a protocol for secure mining of association rules in horizontally distributed da...
Abstract: Data mining is used to extract important knowledge from large datasets, but sometimes thes...
Abstract: Data mining is the most fast growing area today which is used to extract important knowled...
Abstract — The mainstay of this project is to propose a protocol for to reduce data leakage in horiz...
Data mining is used to discovering useful patterns hidden in a database from large datasets, but som...
Security is the important paradigmin data rule mining projects. This project addresses the problem o...
Data mining techniques can extract hidden but useful information from large databases. Most efficien...
A distributed database system is a collection of sites connected on a common high bandwidth network....
These protocols are based on two main approaches named as: the Randomization approach and the Crypto...
Abstract:Association rule learning is a popular and well researched method for discovering interesti...
We study the problem of privacy-preservation in social networks. We consider the distributed setting...
In this paper, we present a new algorithm called Distributed data access control algorithm using ass...
Data mining is the Data mining is the analysis step of the "Knowledge Discovery in Databases" proces...
With the existence of many large transaction databases, the huge amounts of data, the high scalabili...
Abstract — Data mining can extract important knowledge from large data collections – but sometimes t...
Abstract—We propose a protocol for secure mining of association rules in horizontally distributed da...
Abstract: Data mining is used to extract important knowledge from large datasets, but sometimes thes...
Abstract: Data mining is the most fast growing area today which is used to extract important knowled...
Abstract — The mainstay of this project is to propose a protocol for to reduce data leakage in horiz...
Data mining is used to discovering useful patterns hidden in a database from large datasets, but som...
Security is the important paradigmin data rule mining projects. This project addresses the problem o...
Data mining techniques can extract hidden but useful information from large databases. Most efficien...
A distributed database system is a collection of sites connected on a common high bandwidth network....
These protocols are based on two main approaches named as: the Randomization approach and the Crypto...
Abstract:Association rule learning is a popular and well researched method for discovering interesti...
We study the problem of privacy-preservation in social networks. We consider the distributed setting...
In this paper, we present a new algorithm called Distributed data access control algorithm using ass...
Data mining is the Data mining is the analysis step of the "Knowledge Discovery in Databases" proces...
With the existence of many large transaction databases, the huge amounts of data, the high scalabili...
Abstract — Data mining can extract important knowledge from large data collections – but sometimes t...