An Efficient Privacy Preserving in MSN using Improved Decision Tree Algorithm

نویسندگان

  • Neetu Raghuwanshi
  • Abhishek Mathur
  • Soumen Chakrabarti
  • Byron Dom
  • David Gibson
  • Jon Kleinberg
  • S. Ravi Kumar
  • Prabhakar Raghavan
  • Sridhar Rajagopalan
  • Andrew Tomkins
  • Liaoruo Wang
  • Tiancheng Lou
  • Jie Tang
  • John E. Hopcroft
  • Alan Mislove
  • Massimiliano Marcon
  • Krishna P. Gummadi
  • Peter Druschel
  • Walter Willinger
  • Reza Rejaie
  • Mojtaba Torkjazi
  • Masoud Valafar
  • Mauro Maggioni
  • Yaping Li
  • Minghua Chen
  • Qiwei Li
  • Wei Zhang
  • Bart Kuijpers
  • Vanessa Lemmens
  • Bart Moelans
  • Alka Gangrade
  • Ravindra Patel
  • Lan Zhang
  • Kebin Liu
  • Yunhao Liu
چکیده

Here in this paper, efficient privacy preservation over Mobile Social Networks is implemented to secure attacks over Mobile Social Networks. The Existing methodology implemented for the Friending Mobile Social Networks is efficient which provides an efficient computation of Data and privacy from unauthorized users. Here an efficient Decision Tree based algorithm is implemented using Partition of Data using Some Partition based algorithm and then classify data using an ID3 algorithm. The Experimental results when performed on Social Network Dataset the proposed methodology gives efficient results in comparison.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Building Privacy-preserving C4.5 Decision Tree Classifier on Multi- Parties

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 a...

متن کامل

Privacy Preserving Data Mining in Electronic Health Record using K- anonymity and Decision Tree

In this paper, we present an accurate and efficient privacy preserving data mining technique in Electronic Health Record (EHR) by using k –anonymity and decision tree C4.5 that is useful to generate pattern for medical research or any clinical trials. It is analyzed that anonymization offers better privacy rather than other privacy preserving method like that randomization, cryptography, pertur...

متن کامل

Privacy-Preserving Imputation of Missing

Handling missing data is a critical step to ensuring good results in data mining. Like most data mining algorithms, existing privacy-preserving data mining algorithms assume data is complete. In order to maintain privacy in the data mining process while cleaning data, privacy-preserving methods of data cleaning will be required. In this paper, we address the problem of privacy-preserving data i...

متن کامل

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 کامل

Privacy - preserving imputation of missing data q

Handling missing data is a critical step to ensuring good results in data mining. Like most data mining algorithms, existing privacy-preserving data mining algorithms assume data is complete. In order to maintain privacy in the data mining process while cleaning data, privacy-preserving methods of data cleaning are required. In this paper, we address the problem of privacy-preserving data imput...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017