Classification and Evaluation of Privacy Preserving Data Mining Methods

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

NASIRI NEGAR; KEYVANPOUR MOHAMMAD REZA

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: International Journal of Information and Communication Technology Research Year:2020 | Volume:12 | Issue:3 Page(s): 27-37

Download Full-Text

View:

115

Download:

Cites:

Information Journal Paper

Title

Classification and Evaluation of Privacy Preserving Data Mining Methods

Author(s)

NASIRI NEGAR | KEYVANPOUR MOHAMMAD REZA | Issue Writer Certificate

Keywords

Information

Privacy

Data Mining

Privacy preserving Data Mining

PPDM

Abstract

In the last decades a huge number of Information is produced per hour. This collected data can be used in some different fields such as business, healthcare, cybersecurity, after some process etc. in step two, the important process is that when this data is gathered, extraction of useful knowledge should be done from raw Information. But the challenge that we face within this process, is the sensitivity of this Information, which has made owners reluctant to share their sensitive Information. This has led the study of the Privacy of data in Data Mining to be a hot topic today. In this paper, an attempt is made to provide a framework for qualitative analysis of methods. This qualitative framework consists of three main sections: a comprehensive classification of proposed methods, proposed evaluation criteria, and their qualitative evaluation. In this case, we have a most important purpose of presenting this framework: 1) systematic introduction of the most important methods of Privacy-preserving in Data Mining 2) creating a suitable platform for qualitative comparison of these methods 3) providing the possibility of selecting methods appropriate to the needs of application areas 4) systematic introduction of points Weakness of existing methods as a prerequisite for improving methods of PPDM.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

NASIRI, NEGAR, & KEYVANPOUR, MOHAMMAD REZA. (2020). Classification and Evaluation of Privacy Preserving Data Mining Methods. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH, 12(3), 27-37. SID. https://sid.ir/paper/969983/en

Vancouver: Copy

NASIRI NEGAR, KEYVANPOUR MOHAMMAD REZA. Classification and Evaluation of Privacy Preserving Data Mining Methods. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH[Internet]. 2020;12(3):27-37. Available from: https://sid.ir/paper/969983/en

IEEE: Copy

NEGAR NASIRI, and MOHAMMAD REZA KEYVANPOUR, “Classification and Evaluation of Privacy Preserving Data Mining Methods,” INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGY RESEARCH, vol. 12, no. 3, pp. 27–37, 2020, [Online]. Available: https://sid.ir/paper/969983/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops