A new auditing scheme for securing statistical databases

Elshiekh, Asim Abdallah; Dominic, P. D. D.

doi:10.1109/itsim.2008.4631562

Cited by 7 publications

(6 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a continuation to the previous work of the authors [4] [5], this paper proceeds with the presentation of an auditing method that can be used to repel the attacks of the snooper to the confidentiality of the individual data in the SDB. We propose three audit stages to protect online and dynamic SDBs from being disclosed.…”

Section: Audit Stagesmentioning

confidence: 97%

“…Each employee is classified in three categories and has one data attribute. The possible category attributes' values are as follows: Table II shows the key representation database (KRDB) D \ [4], which the conversion result of the original database D by converting the three category attributes (Gender, Dept, Level) into one cell (U i1 U i2 U i3 ), and the data attribute value V i1 will be separated by the sign '.'. The converted two cells are as following:…”

Section: Introductionmentioning

confidence: 99%

“…The authors in [4] provide the statistical database model for this scheme. They assume that the original database D contains N records of individuals; each record has t category attributes and d data attributes (A 1 , A 2 , … , A t , A t+1 , A t+2 , … , A t+d ).…”

Section: Introductionmentioning

confidence: 99%

“…A general tracker's query set size must fall in the range [2n, N-2n][7][8], that is[4,8] with n=2 and N=12. The formula T = M qualifies as a general tracker since | T | = 7.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Cost Estimation for the Key Representation Auditing Scheme

Elshiekh

Dominic

2009

2009 International Conference on Signal Processing Systems

View full text Add to dashboard Cite

A statistical database (SDB) publishes statistical queries (such as sum, average, count, etc) on subsets of records, and the data in individual records should be remained secret.The key representation auditing scheme is proposed to guarantee the security of online and dynamic SDBs. The core idea is to convert the original database into key representation database (KRDB), also this scheme involves converting each new user query from string representation into key representation query (KRQ), and stores it in the Audit Query table (AQ table). We propose three audit stages to repel the attacks of the snooper to the confidentiality of the individuals. These stages enable the key representation auditor (KRA) to conveniently specify the illegal queries which could lead to disclosing the SDB. Cost estimation for this scheme is performed, and we illustrate the saving in block accesses (CPU time) and storage space that are attainable when a KRDB is used.

show abstract

Section: Audit Stagesmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…A general tracker's query set size must fall in the range [2n, N-2n][7][8], that is[4,8] with n=2 and N=12. The formula T = M qualifies as a general tracker since | T | = 7.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Cost Estimation for the Key Representation Auditing Scheme

Elshiekh

Dominic

2009

2009 International Conference on Signal Processing Systems

View full text Add to dashboard Cite

show abstract

“…Query auditing was introduced in 1976 [12], [20] to check for possible compromises when a database is queried or shared. It remains an active research area [8] [7] [18] [15]. Unlike this work, most work in this area focuses on protecting privacy of entries in a database when aggregate statistical queries such as mean, sum and max are allowed over the whole database.…”

Section: Related Workmentioning

confidence: 99%

Auditing Information Leakage for Distance Metrics

Chen

Evans

2011

2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing

View full text Add to dashboard Cite

Abstract-Many useful scenarios involve allowing untrusted users to run queries against secret data, so long as the results do not leak too much information. This problem has been studied widely for statistical queries, but not for queries with more direct semantics. In this paper, we consider the problem of auditing queries where the result is a distance metric between the query input and some secret data. We develop an efficient technique for estimating a lower bound on the entropy remaining after a series of query-responses that applies to a class of distance functions including Hamming distance. We also present a technique for ensuring that no individual bits of the secret sequence is leaked. In this paper, we formalize the information leakage problem, describe our design for a query auditor, and report on experiments showing the feasibility and effectiveness of our approach for sensitive sequences up to thousands of bits.

show abstract

Three Audit Stages for Securing Statistical Databases

Elshiekh

Dominic

2009

2009 International Conference on Information Management and Engineering

View full text Add to dashboard Cite

A new auditing scheme for securing statistical databases

Cited by 7 publications

References 12 publications

Cost Estimation for the Key Representation Auditing Scheme

Cost Estimation for the Key Representation Auditing Scheme

Auditing Information Leakage for Distance Metrics

Three Audit Stages for Securing Statistical Databases

Contact Info

Product

Resources

About