  Systems that employ network coding for content distribution convey to the
receivers linear combinations of the source packets. If we assume randomized
network coding, during this process the network nodes collect random subspaces
of the space spanned by the source packets. We establish several fundamental
properties of the random subspaces induced in such a system, and show that
these subspaces implicitly carry topological information about the network and
its state that can be passively collected and inferred. We leverage this
information towards a number of applications that are interesting in their own
right, such as topology inference, bottleneck discovery in peer-to-peer systems
and locating Byzantine attackers. We thus argue that, randomized network
coding, apart from its better known properties for improving information
delivery rate, can additionally facilitate network management and control.
