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Contributor III

Re-identification easier than was thought

Next time you think you've anonymised that big data set by removing obvious identifiers, look more closely:

 

https://www.theguardian.com/technology/2019/jul/23/anonymised-data-never-be-anonymous-enough-study-f...

 

 

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Steve Wilme CISSP-ISSAP, ISSMP MCIIS
3 Replies
Advocate I

Re: Re-identification easier than was thought


@Steve-Wilme wrote:

https://www.theguardian.com/technology/2019/jul/23/anonymised-data-never-be-anonymous-enough-study-f...

 


I'm glad to see that the original Working Party 29 Anonymisation Techniques are getting a fresh new research perspective. How data is shared today between partner organizations and data brokers is totally broken. Recently, Google has tried to make its implementation of Private Join and Compute publicly accessible through a GitHub repo but it remains to be seen who is adopting the techniques...

Tags (1)
Contributor III

Re: Re-identification easier than was thought

The UKAN decision making framework is a useful resource in this area:

https://ukanon.net/ukan-resources/ukan-decision-making-framework/

 

I've yet to find a developer or big data analytics person who's actually read it though Smiley Sad

 

 

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Steve Wilme CISSP-ISSAP, ISSMP MCIIS
Advocate I

Re: Re-identification easier than was thought


@Steve-Wilme wrote:

The UKAN decision making framework is a useful resource in this area:

https://ukanon.net/ukan-resources/ukan-decision-making-framework/

 

I've yet to find a developer or big data analytics person who's actually read it though Smiley Sad

 


You just found a CSSLP that has read and preaches this guidance! What I do differently though to complement the framework is teach how-to implement anonymisation algorithms, design UI's that are privacy-preserving. and design data sharing mechanisms. That is what developers and statisticians care about. Implementing code!