Abstract
This article explores the potential of data mining as a technique that could be used by malicious data miners to threaten the privacy of Social Network Sites (SNSs) users. It applies a data mining algorithm, specifically a clustering algorithm, to a hypothetical dataset to show the ease at which characteristics about the SNSs users can be discovered and used in a way that could invade their privacy. One important outcome of exploring the threats from data mining on individuals’ privacy is enable SNSs developers better understand the ways in which SNSs can be used by malevolent data miners to harm users. Another important outcome is to help developers of SNSs develop mechanisms that will provide protection to users from these knowledge discovery techniques.
Original language | English |
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Pages (from-to) | 29-34 |
Number of pages | 6 |
Journal | World Journal of Computer Application and Technology |
Volume | 1 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2013 |