eprintid: 2341
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/23/41
datestamp: 2023-11-09 15:50:33
lastmod: 2023-11-09 15:50:33
status_changed: 2023-11-09 15:42:32
type: article
metadata_visibility: show
creators_name: Elshiekh, A.A.
creators_name: Dominic, P.D.D.
title: Statistical analysis for comparison of the key representation database with the original database
ispublished: pub
note: cited By 0
abstract: Statistical databases (SDBs) are used mainly for statistics, and individuals' information should remain secret. Key representation auditing scheme (KRAS) is proposed to guard individuals' confidentiality in online and dynamic SDBs. KRAS converts the original database into key representation database (KRDB) and each new query should be converted into key representation query. Three audit stages are proposed to guarantee the security of SDBs. Also, cost estimation for this scheme is performed, and we illustrate the savings in CPU time and storage space using KRDB. In this paper, we provide statistical analysis for comparison of original database with KRDB to compare between the means/variances of the original database and the KRDB populations. Comparisons are provided in terms of linear search, binary search and sorting. The results of the tests showed that the differences are statistically significant, except in one case, namely the differences between the variances in terms of binary search. Copyright © 2011 Inderscience Enterprises Ltd.
date: 2011
publisher: Inderscience Publishers
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052670561&doi=10.1504%2fIJBIS.2011.042395&partnerID=40&md5=adea0f60a4f5134bc50bf203043931f8
id_number: 10.1504/IJBIS.2011.042395
full_text_status: none
publication: International Journal of Business Information Systems
volume: 8
number: 4
pagerange: 339-360
refereed: TRUE
issn: 17460972
citation:   Elshiekh, A.A. and Dominic, P.D.D.  (2011) Statistical analysis for comparison of the key representation database with the original database.  International Journal of Business Information Systems, 8 (4).  pp. 339-360.  ISSN 17460972