Survey on Association Rule Hiding Techniques

Autor:	S. Sivakumari, G. Bhavani
Rok vydání:	2019
Předmět:	Computer science 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 02 engineering and technology Data mining Association rule hiding computer.software_genre computer
Zdroj:	International Journal of Scientific Research in Science, Engineering and Technology. :300-305
ISSN:	2394-4099 2395-1990
DOI:	10.32628/ijsrset196368
Popis:	Data mining process extracts useful information from a large amount of data. The most interesting part of data mining is discovering the unseen patterns without unpacking sensitive knowledge. Privacy Preserving Data Mining abbreviated as PPDM deals with the issue of sustaining the privacy of information. This methodology covers the sensitive information from disclosure. PPDM techniques are established for hiding the sensitive information even after performing the data mining. One of the practices to hide the sensitive association rules is termed as association rule hiding. The main objective of association rule hiding algorithm is to slightly adjust the original database so that no sensitive association rule is derived from it. The following article presents a detailed survey of various association rule hiding techniques for preserving privacy in data mining. At first, different techniques developed by previous researchers are studied in detail. Then, a comparative analysis is carried out to know the limitations of each technique and then providing a suggestion for future improvement in association rule hiding for privacy preservation.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ec1efcd35a1d59351aa8e153a128d04e https://doi.org/10.32628/ijsrset196368 Zobrazit plný text záznamu