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Yangfend Qu, Illinois Institute of Technology, Xin Liu, Illinois Institute of Technology, Dong Jin, Illinois Institute of Technology, Yuan Hong, Illinois Institute of Technology, Chen Chen, Argonne National Laboratory.  2018.  Enabling a Resilient and Self-healing PMU Infrastructure Using Centralized Network Control. 2018 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization.

Many of the emerging wide-area monitoring protection and control (WAMPAC) applications in modern electrical grids rely heavily on the availability and integrity of widespread phasor measurement unit (PMU) data. Therefore, it is critical to protect PMU networks against growing cyber-attacks and system faults. In this paper, we present a self-healing PMU network design that considers both power system observability and communication network characteristics. Our design utilizes centralized network control, such as the emerging software-defined networking (SDN) technology, to design resilient network self-healing algorithms against cyber-attacks. Upon detection of a cyber-attack, the PMU network can reconfigure itself to isolate compromised devices and re-route measurement
data with the goal of preserving the power system observability. We have developed a proof-of-concept system in a container-based network testbed using integer linear programming to solve a graphbased PMU system model.We also evaluate the system performance regarding the self-healing plan generation and installation using the IEEE 30-bus system.

Kurilova, Darya, Omar, Cyrus, Nistor, Ligia, Chung, Benjamin, Potanin, Alex, Aldrich, Jonathan.  2014.  Type-specific Languages to Fight Injection Attacks. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :18:1–18:2.

Injection vulnerabilities have topped rankings of the most critical web application vulnerabilities for several years [1, 2]. They can occur anywhere where user input may be erroneously executed as code. The injected input is typically aimed at gaining unauthorized access to the system or to private information within it, corrupting the system's data, or disturbing system availability. Injection vulnerabilities are tedious and difficult to prevent.