Privacy and Data Mining

So I was on a panel in Washington DC last week in a workshop on Privacy and Data Mining for Department of Homeland Security.  The topic, of course, can be quite incendiary.  But the focus of the panel was on privacy preserving data mining technology, so we kept the discussion at a technical level and avoided politics or policy.

The points I made on the panel (other panelists were Chris Clifton from Purdue, and Rebecca Wright from DIMACS and Rutgers) were the following

1. Commercial businesses are very much interested in this too, and this interest is driving technology innovation that can be leveraged in DHS situations.
2. While data mining and privacy preserving aspects of it have the fiery appeal, the fact is that privacy preservation is critical across all aspects of a data lifecycle -- data at rest, data in motion, data graveyard, test, production, integration etc. -- many copies of data existing before and after the data mining. Consequently, having bullet-proof privacy preservation in the data mining "part" of this chain is not sufficient.
3. That IBM and other vendors have built up a repertoire of capabilities, primarily from a commercial perspective.  I highlighted the research of Hippocratic Databases and the privacy preserving technologies in our Entity Analytics Solutions as two sets of examples of these.

It is always risky wading into such controversial topics, but I enjoyed the panel very much, learnt from the other panelists, and equally importantly, learnt from other panels.  I think such dialogs are critical. 

I want to especially thank Tyrone Grandison, Alexandre Evfimievski, Jeff Jonas, Katie Ignaszewski

and our Chief Privacy Officer, Harriet Pearson, for helping me with the talk and the panel.