Building Privacy-preserving C4.5 Decision Tree Classifier on Multi- Parties
نویسندگان
چکیده
In this paper, we address Privacy-preserving classification problem in a multi-party sense. We focus the general classification in a secured manner and introduce a Privacy-preserving decision tree classifier using C4.5 algorithm without involving third party. C4.5 algorithm is a software extension of the basic ID3 algorithm designed by Quinlan. Our protocol is considerably more efficient than any existing solutions.
منابع مشابه
Decision Tree Classifier for Privacy Preservation
In recent year’s privacy preservation in data mining has become an important issue. A new class of data mining method called privacy preserving data mining algorithm has been developed. The aim of these algorithms is to protect the sensitive information in data while extracting knowledge from large amount of data. We focus the general classification in a secured manner and introduce a privacy-p...
متن کاملPrivacy-Preserving Decision Tree Classification Over Horizontally Partitioned Data
Protection of privacy is one of important problems in data mining. The unwillingness to share their data frequently results in failure of collaborative data mining. This paper studies how to build a decision tree classifier under the following scenario: a database is horizontally partitioned into multiple pieces, with each piece owned by a particular party. All the parties want to build a decis...
متن کاملA Novel Protocol For Privacy Preserving Decision Tree Over Horizontally Partitioned Data
In recent times, there have been growing interests on how to preserve the privacy in data mining when sources of data are distributed across multi-parties. In this paper, we focus on the privacy preserving decision tree classification in multi-party environment when data are horizontally partitioned. We develop new and simple algorithm to classify the horizontally partitioned multi-party data. ...
متن کاملPrivacy-Preserving Self-Organizing Map
Privacy-preserving data mining seeks to allow the cooperative execution of data mining algorithms while preserving the data privacy of each party concerned. In recent years, many data mining algorithms have been enhanced with privacy-preserving feature: decision tree induction, frequent itemset counting, association analysis, k-means clustering, support vector machine, Näıve Bayes classifier, B...
متن کاملPrivacy-Preserving Classification and Clustering Using Secure Multi-Party Computation
Nowadays, data mining and machine learning techniques are widely used in electronic applications in different areas such as e-government, e-health, e-business, and so on. One major and very crucial issue in these type of systems, which are normally distributed among two or more parties and are dealing with sensitive data, is preserving the privacy of individual’s sensitive information. Each par...
متن کامل