NS Seminar

Date and Location

May 25, 2018 - 1:00pm to 2:00pm
Bldg 434, room 122


Synchronization and power sharing for droop-controlled inverters in islanded microgrids (presented by Kevin Smith, Electrical and Computer Engineering)

Simpson-Porco, J. W., Dörfler, F., & Bullo, F. (2013). Synchronization and power sharing for droop-controlled inverters in islanded microgrids. Automatica, 49(9), 2603-2611.

Motivated by the recent and growing interest in smart grid technology, we study the operation of DC/AC inverters in an
inductive microgrid. We show that a network of loads and DC/AC inverters equipped with power-frequency droop controllers
can be cast as a Kuramoto model of phase-coupled oscillators. This novel description, together with results from the theory
of coupled oscillators, allows us to characterize the behavior of the network of inverters and loads. Specifically, we provide a
necessary and sufficient condition for the existence of a synchronized solution that is unique and locally exponentially stable.
We present a selection of controller gains leading to a desirable sharing of power among the inverters, and specify the set
of loads which can be serviced without violating given actuation constraints. Moreover, we propose a distributed integral
controller based on averaging algorithms, which dynamically regulates the system frequency in the presence of a time-varying
load. Remarkably, this distributed-averaging integral controller has the additional property that it preserves the power sharing
properties of the primary droop controller. Our results hold without assumptions on identical line characteristics or voltage


Adversarial network forensics in software defined networking (presented by Abe Karplus, Computer Science)

Achleitner, S., La Porta, T., Jaeger, T., & McDaniel, P. (2017, April). Adversarial network forensics in software defined networking. In Proceedings of the Symposium on SDN Research (pp. 8-20). ACM.

Software Defined Networking (SDN), and its popular implementation OpenFlow, represent the foundation for the design and implementation of modern networks. The essential part of an SDN-based network are flow rules that enable network elements to steer and control the traffic and deploy policy enforcement points with a fine granularity at any entry-point in a network. Such applications, implemented with the usage of OpenFlow rules, are already integral components of widely used SDN controllers such as Floodlight or OpenDayLight. The implementation details of network policies are reflected in the composition of flow rules and leakage of such information provides adversaries with a significant attack advantage such as bypassing Access Control Lists (ACL), reconstructing the resource distribution of Load Balancers or revealing of Moving Target Defense techniques.

In this paper we introduce a new attack vector on SDN by showing how the detailed composition of flow rules can be reconstructed by network users without any prior knowledge of the SDN controller or its architecture. To our best knowledge, in SDN, such reconnaissance techniques have not been considered so far. We introduce SDNMap, an open-source scanner that is able to accurately reconstruct the detailed composition of flow rules by performing active probing and listening to the network traffic. We demonstrate in a number of real-world SDN applications that this ability provides adversaries with a significant attack advantage and discuss ways to prevent the introduced reconnaissance techniques. Our SDNMap scanner is able to reconstruct flow rules between network endpoints with an accuracy of over 96%.