Proceedings of the 2015 International conference on Applied Science and Engineering Innovation

Research on the effective detection method of specific data in large database

Authors
Jin-feng Li
Corresponding Author
Jin-feng Li
Available Online May 2015.
DOI
10.2991/asei-15.2015.97How to use a DOI?
Keywords
large database; specific data; frequent sets;
Abstract

the effective detection of specific data for large databases can ensure the security of large data. Because of the strong subjectivity of the traditional detection method, the accuracy of detection and the detection efficiency are decreased. To this end, a specific data detection method based on Apriori algorithm for large databases is proposed. The characteristics of specific data nodes is calculated to provide data base for the detection of specific data. To find out the frequent sets of all the specific data, the frequent sets are obtained strong association rules meet the minimum support degree and the minimum reliability, and then the detection of the specific data in large database is completed. Experimental results show that the detection of specific data of large database can be effectively improved by using the improved algorithm, the accuracy and detection efficiency of the detection are increased as well.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
Series
Advances in Engineering Research
Publication Date
May 2015
ISBN
10.2991/asei-15.2015.97
ISSN
2352-5401
DOI
10.2991/asei-15.2015.97How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jin-feng Li
PY  - 2015/05
DA  - 2015/05
TI  - Research on the effective detection method of specific data in large database
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 481
EP  - 484
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.97
DO  - 10.2991/asei-15.2015.97
ID  - Li2015/05
ER  -