Time Inference Attacks on Software Defined Networks: Challenges and Countermeasures

摘要

Through time inference attacks, adversaries fingerprint SDN controllers, estimate switches flow-table size, and perform flow state reconnaissance. In fact, timing a SDN and analyzing its results can expose information which later empowers SDN resource-consumption or saturation attacks. In the real world, however, launching such attacks is not easy. This is due to some challenges attackers may encounter while attacking an actual SDN deployment. These challenges, which are not addressed adequately in the related literature, are investigated in this paper. Accordingly, practical solutions to mitigate such attacks are also proposed. Discussed challenges are clarified by means of conducting extensive experiments on an actual cloud data center testbed. Moreover, mitigation schemes have been implemented and examined in details. Experimental results show that proposed countermeasures effectively block time inference attacks.