data confidentiality, residual disclosure and risk mitigation
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Data Confidentiality, Residual Disclosure and Risk Mitigation. Joint UNECE/ Eurostat Work Session (Ottawa, Canada, 28-30 October 2013) Raja Hettiarachchi Statistics Department, International Monetary Fund. Overview. Introduction Levels of confidentiality Policies and Procedures - PowerPoint PPT PresentationTRANSCRIPT
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Data Confidentiality, Residual Disclosure and Risk Mitigation
Joint UNECE/Eurostat Work Session(Ottawa, Canada, 28-30 October 2013)
Raja HettiarachchiStatistics Department, International Monetary Fund
Statistics Department
Overview
Introduction
Levels of confidentiality
Policies and Procedures
IT implementations
Challenges
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Statistics Department
Introduction IMF Statistics Department (STA) collects data from national
authorities as well as international and regional organizations.
As a global institution entrusted with highly confidential data by national authorities, IMF has no margin for error in regard to disclosing sensitive information.
STA has broadly categorized the levels of confidentiality of the data it manages and has established policies, procedures, and systems to safeguard sensitive information from misuse, while increasing the efforts to improve data utility
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Statistics Department
Levels of Confidentiality Data reported only for internal analysis and/or calculation of
global and regional aggregates
Data Series suppressed by authorities to protect confidentiality
Data Observations suppressed by authorities
Internal estimates treated as confidential data
Global and Regional aggregates suppressed to protect individual data reporters
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Statistics Department
Policies and Procedures Policies
Comply with data control policies implemented at national level Comply with internal statistical disclosure controls Authorities are encouraged to suppress confidential data
observations prior to reporting to the Fund Only on rare occasions IMF will omit series or suppress reported
data observations
Procedures Only authorized staff has access rights to sensitive data Tend to over delete secondary data cells to mitigate risk of residual
disclosure Validations and re-edits to improve data utility
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Statistics Department
IT Implementations Access level restrictions
Omissions For countries that have established patterns of data suppressions, and
the required secondary suppressions are already analyzed, secondary data series will be omitted at the time of data load.
Suppressions of Aggregates Dominance rule (largest reporter = 80% of total, two largest = 90%) Depend on number of reporters
Suppression of primary and secondary cells Data re-edits for improve usability
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Statistics Department
Access Level Restrictions
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Access RestrictedProduction Database
Dissemination Database
Available only for authorized staff
Database is hard coded to receive only authorized time series to prevent accidental disclosure of sensitive information
Statistics Department
D+ Delete all calculated values (resultants) of the primary data delete
Use the equation graph (formula tree) of the database system; All resultants of the primary data delete are deleted
D* Delete all consolidated values of the primary data deleteUse the consolidation method of each data series (e.g., delete of a monthly
data value will result in the delete of quarterly and annual values)
D+* Delete all calculated and consolidated values of the primary data delete
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Secondary Data Cell DeletesUsing D+, D*, D+*
Statistics Department
Data Cell Deletes Using D+Delete All Calculated Values (Resultants)
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D+
Statistics Department
Data Cell Deletes using D* Delete All Consolidated Values
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D*D*
Statistics Department
Data Cell Deletes using D+*Delete All Calculated and Consolidated Secondary Cells
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D+*
Statistics Department
Data re-edits to improve usability if more than one sub aggregate is suppressed
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D+*
D+*
5907 19416
Statistics Department
Challenges Growing demand for full disclosure
Difficult to coordinate a concerted effort to release sensitive data
Integrate secondary deletes, validations, and re-edits to optimize the data utility
System developments and testing of restricted databases
Difficult to manage user expectations due to specific nature of national statistical disclosure policies and revision policies
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Statistics Department
Proper management of sensitive information and protection of confidential data are major concerns for the IMF Statistics Department.
There are ongoing efforts to disseminate as much information as possible while mitigating disclosure risks.
Thank youQuestions?
Raja [email protected]
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