Inference Attacks

Phil Factor explains that your technique for pseudonymizing data doesn’t necessarily anonymize the data:

It is possible to mine data for hidden gems of information by looking at significant patterns of data. Unfortunately, this sometimes means that published datasets can reveal sensitive data when the publisher didn’t intend it, or even when they tried to prevent it by suppressing any part of the data that could enable individuals to be identified

Using creative querying, linking tables in ways that weren’t originally envisaged, as well as using well-known and documented analytical techniques, it’s often possible to infer the values of ‘suppressed’ data from the values provided in other, non-suppressed data. One man’s data mining is another man’s data inference attack.

Read the whole thing.  One big problem with trying to anonymize data is that you don’t know how much the attacker knows.  Especially with outliers or smaller samples, you might be able to glean interesting information with a series of queries.  Even if the application only returns aggregated results for some N, you can often put together a set of queries where you slice the population different ways until you get hidden details on individual.  Phil covers these types of inference attacks.

Related Posts

SQL Server Agent Security

Claudio Silva explains how you can provide secure access to manage SQL Agent jobs: It is common having services accounts that are job owners so they can run within the proper context. In my humble opinion, this starts to be a little strange when it comes to modifying the agent job. It means that the […]

Read More

Storing Passwords in the Database

Randolph West explains the problems with storing passwords in the database and explains the best alternative: If you are storing passwords in a database, you should stop doing that immediately. We, as software developers and data professionals, should never know what passwords our customers are using. The same goes for most sensitive data: we technical […]

Read More

Categories

August 2017
MTWTFSS
« Jul Sep »
 123456
78910111213
14151617181920
21222324252627
28293031