TY - GEN
T1 - Misreporting attacks in software-defined networking
AU - Burke, Quinn
AU - McDaniel, Patrick
AU - Porta, Thomas La
AU - Yu, Mingli
AU - He, Ting
N1 - Funding Information:
Acknowledgements. This research was sponsored by the U.S. Army Combat Capabilities Development Command Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-13-2-0045 (ARL Cyber Security CRA). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Combat Capabilities Development Command Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. This work was also supported in part by the National Science Foundation under award CNS-1946022.
PY - 2020
Y1 - 2020
N2 - Load balancers enable efficient use of network resources by distributing traffic fairly across them. In software-defined networking (SDN), load balancing is most often realized by a controller application that solicits traffic load reports from network switches and enforces load balancing decisions through flow rules. This separation between the control and data planes in SDNs creates an opportunity for an adversary at a compromised switch to misreport traffic loads to influence load balancing. In this paper, we evaluate the ability of such an adversary to control the volume of traffic flowing through a compromised switch by misreporting traffic loads. We use a queuing theoretic approach to model the attack and develop algorithms for misreporting that allow an adversary to tune attack parameters toward specific adversarial goals. We validate the algorithms with a virtual network testbed, finding that through misreporting the adversary can draw nearly all of the load in the subnetwork (+750%, or 85% of the load in the system), or an adversary-desired amount of load (a target load, e.g., +200%) to within 12% error of that target. This is yet another example of how depending on untrustworthy reporting in making control decisions can lead to fundamental security failures.
AB - Load balancers enable efficient use of network resources by distributing traffic fairly across them. In software-defined networking (SDN), load balancing is most often realized by a controller application that solicits traffic load reports from network switches and enforces load balancing decisions through flow rules. This separation between the control and data planes in SDNs creates an opportunity for an adversary at a compromised switch to misreport traffic loads to influence load balancing. In this paper, we evaluate the ability of such an adversary to control the volume of traffic flowing through a compromised switch by misreporting traffic loads. We use a queuing theoretic approach to model the attack and develop algorithms for misreporting that allow an adversary to tune attack parameters toward specific adversarial goals. We validate the algorithms with a virtual network testbed, finding that through misreporting the adversary can draw nearly all of the load in the subnetwork (+750%, or 85% of the load in the system), or an adversary-desired amount of load (a target load, e.g., +200%) to within 12% error of that target. This is yet another example of how depending on untrustworthy reporting in making control decisions can lead to fundamental security failures.
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U2 - 10.1007/978-3-030-63086-7_16
DO - 10.1007/978-3-030-63086-7_16
M3 - Conference contribution
AN - SCOPUS:85098279259
SN - 9783030630850
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 276
EP - 296
BT - Security and Privacy in Communication Networks - 16th EAI International Conference, SecureComm 2020, Proceedings
A2 - Park, Noseong
A2 - Sun, Kun
A2 - Foresti, Sara
A2 - Butler, Kevin
A2 - Saxena, Nitesh
PB - Springer Science and Business Media Deutschland GmbH
T2 - 16th International Conference on Security and Privacy in Communication Networks, SecureComm 2020
Y2 - 21 October 2020 through 23 October 2020
ER -