PSEUDONYMIZATION TECHNIQUES FOR PRIVACY STUDY WITH CLINICAL DATA 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

Introduction  What 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. 3

Literature Review Data Protection Techniques 4 Protection (Data) Encrypt Anonymity Application Source : IHSN ( June 2009) Purpose : Security & Privacy Pseudonymization

Literature Review Issues: Data Privacy Area 5 Privacy (Data) Anonymous communication Anonymous transactions Anonymity in Files & Databases Purpose : Privacy Anonymous Credentials Anonymous Publication & Storage

Literature Review Issues: Data Privacy Medical Application Elements 6 Privacy (Data) “Hard” de- identification Various Types Anonymization Data Flow Segmentation Purpose : Privacy Controlled Database Privacy Risk Assessment

Literature Review Why Data Need To Anonymous? Publish Anonymous Process Researcher (Customize) Pattern / Predict (Customize) Advertise (Customize) Information Loss Leak - Privacy Incur ProblemSecurity (Pure)

Literature Review Issues : 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). 8

Problem Statement 9 Most anonymous process may cause privacy leakage with the original data from user information. Chances of loss information in most anonymous process is high.

Scope The scope of this research are:  Implemented the pseudonymization techniques from anonymous process with medical clinical data.  Using data in offline mode. 10

Pseudonymization Techniques 11  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

12 Data Privacy (Domain) Data Reduction Data Perturbation Data synthetic Dataset Anonymous dataset Pseudonymization Process Flow On Research Methodology

Pseudonymization Implementations 13 Privacy Protection Data Suppliers (sources)Data Collectors (data registers)

Pseudonymization Implementations: Architecture 14

15 Data Public Pseudonymization Engine AnonymizerRisk Analyzer Data Storage Source : Enhanced Simplifying Anonymizing Proxy, Saikat Guha, Pseudonymization Implementations

Result View (RO4) 16 Density Of Information Source: Statistic IHSN, 2009 Black Marker, Truncation

Conclusion It 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. 17

Future Work 18 Generalization Process In Pseudonymization  Micro data e.g: Medical data  Network data Online Anonymization Process as Alternative Beside Encryption

end Thank you….. 19