Naslov
Privacy preserving in data mining – experimental research on SMEs data

Autori
Grljević, Olivera ; Bošnjak, Zita ; Mekovec Renata

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceeding of the SISY 2011 9th IEEE International Symposium on Intelligent Systems and Informatics / - , 2011, 477-481

ISBN
978-1-4577-1973-8

Skup
SISY 2011 9th IEEE International Symposium on Intelligent Systems and Informatics

Mjesto i datum
Subotica, Srbija, 08.09.2011. - 10.09.2011

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
privacy; data mining; privacy preserving techiques

Sažetak
Analysis of data on individuals and business sensitive data as well as revealing the results of such analysis without disclosing confidential and sensitive information is a very important issue. Many techniques for preserving privacy of data are currently being used. In this paper, we addressed the basic techniques: randomization, kanonymity, distributed privacy preserving and application effectiveness downgrading. Most of the techniques should be applied in the phase of data collection or their preprocessing, which can lead to different results (better or worse) of data mining than would be obtained on original data. For this reason, data analysts should be encouraged to quantify the ratio between privacy preserved in data with application of each technique and the loss of data or quality of outputs. In this paper, we illustrated the application of certain techniques for preserving privacy on experimental dataset, and we showed the effects that their use has on the results.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti

POVEZANOST RADA