SNCB Data Leak: Geo-localization of the entries


*UPDATE*: Images below can be used to build up other article if reference is kept back.

Xavier Damman already showed what can be extracted from the SNCB’s leaked data. Now what could be shown with some massive geo-localization of theses data? What would it means to individuals present in the files? How far can we go?

First, let’s examinate a world-view of each entry’s town (Click to enlarge):

World MAP repartition of SNCB Customers

This map aggregate town where SNCB customers have been found inside the leaked file. The bigger the number is on the point, the more town have customers behind the point.

Scary, isn’t it?

We can drill-down that view by focusing on the most used country: Belgium.

Let’s Geo-localize streets this time and put them on a Belgium’s map:

Belgium MAP repartition of SNCB Customers

I will of course not disclose a more drilled-down view, even if having such a view is easy. 

It would also not be hard to add a function to show the personal detail of each marker with a simple click.

How hard would it be to cross-link theses data to public websites like facebook or foursquare? How many leaks like that will we need to start worrying about our private data?

SNCB can be pointed out this time, but it’s not the first leak and certainly not the last! We should all take care of where we put our private data and ensure that organism who handle them do it with care…

Follow me on twitter: @tgouverneur

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