pseudonymization techniques for privacy study with clinical data
DESCRIPTION
PSEUDONYMIZATION TECHNIQUES FOR PRIVACY STUDY WITH CLINICAL DATA. YAHAYA ABD RAHIM FAC.INFORMATION AND COMMUNICATION TECHNOLOGY UNIVERSITY TECHNICAL MALAYSIA MALACCA. Introduction. Hospital, clinic or pharmacy among the organizations that huge of personal data. - PowerPoint PPT PresentationTRANSCRIPT
PSEUDONYMIZATION TECHNIQUES FOR
PRIVACY STUDY WITH CLINICAL DATA
YAHAYA ABD RAHIM
FAC.INFORMATION AND COMMUNICATION TECHNOLOGYUNIVERSITY TECHNICAL MALAYSIA MALACCA
1
Introduction Hospital, clinic or pharmacy among the
organizations that huge of personal data. In new trend , Vijay (2002), these organizations
are interested to release or publish data for research or public benefit like business or legal reasons.
However most of the data are “SENSITIVE”. According to Tiangcheng Li & Ninghui Li (2008),
many organizations, industries and governments are increasingly publishing and sharing the valuable and sensitive information without to protect of the privacy of entities. Publishing the data may put the respondent’s privacy in risk, Ge Ruan (2007).
Focus on techniques for data privacy on clinical data. 2
IntroductionWhat is Privacy?
Privacy includes the right of individuals and organizations to determine for themselves when, how and to what extent information about them is communicated to others.
What Impact with Hospital or Clinical?Challenging with managing large data in
hospital or clinical especially with legal and ethical.
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Literature Review Data Protection Techniques
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Protection
(Data)
Encrypt Anonymi
ty
Application
Source : IHSN ( June 2009)
Purpose : Security & Privacy
Pseudonymization
Literature Review Issues: Data Privacy Area
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Privacy(Data)
Anonymous communicat
ion
Anonymous transactions
Anonymity in Files &
Databases
Purpose : Privacy
Anonymous Credentials
Anonymous Publication & Storage
Literature Review Issues: Data Privacy Medical Application
Elements
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Privacy(Data)
“Hard” de-identificatio
n
Various Types Anonymization
Data Flow Segmentatio
n
Purpose : Privacy
Controlled Database
Privacy Risk Assessment
Literature Review Why Data Need To Anonymous?
PublishAnonymous Process
Researcher(Customize)
Pattern / Predict(Customize)
Advertise(Customize)
• Information Loss
• Leak - Privacy
Incur ProblemSecurity (Pure)
Literature ReviewIssues : Anonymity Technique Most anonymous techniques consist in
reducing the level of detail in the information provided. Therefore, typically most the result in a loss of information, IHSN (2009).
Difficulties into the role of anonymous as a
complete solution to the problem of data protection. It must be considered within the context of the analysis to be done on the data, which information needs to be protect.
Anonymous Process must also be considered within its legal context (Burkhart M., Schatzmann D. & Bernhard P., 2010). But should be the lesser extent for generating licensed files / legal context, IHSN (2009).
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Problem Statement
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Most anonymous process may cause privacy leakage with the original data from user information.
Chances of loss information in most anonymous process is high.
ScopeThe scope of this research are:
Implemented the pseudonymization techniques from anonymous process with medical clinical data.
Using data in offline mode.
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Pseudonymization Techniques
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always map a given identifier with the same pseudo-ID
map a given identifier with a different pseudo-ID
Time-dependent
location-dependent
content-dependent
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Data Privacy(Domain)
Data Reduction
Data Perturbati
onData synthetic
Dataset
Anonymous dataset
Pseudonymization Process
Flow On Research Methodology
Pseudonymization Implementations
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Privacy Protection
Data Suppliers (sources) Data Collectors (data registers)
Pseudonymization Implementations: Architecture
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Data Public
Pseudonymization Engine
Anonymizer Risk Analyzer
Data Storage
Source : Enhanced Simplifying Anonymizing Proxy, Saikat Guha, 2011.
Pseudonymization Implementations
Result View (RO4)
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1 2 3 4 5 6 7 8 9 100
10
20
30
40
50
60Result On Pseudonymization Process
Review TechniqueProposed Technique
Leve
l Of
Priv
acy
Security (Pure)
Density Of Information
Source: Statistic IHSN, 2009
Black Marker, Truncation
ConclusionIt is expected that this research shall produce:
A new technique in anonymous process which more comprehensive where this technique be reduce or none information loss with protection of privacy leakage.
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Future Work
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Generalization Process In Pseudonymization
Micro data e.g: Medical data Network data
• Online Anonymization Process as Alternative Beside Encryption
end Thank you…..
Q & A?19