Factories, chemical plants, automobiles, and aircraft have come to be described today as cyber-physical systems of systems--distinct systems connected to form a larger and more complex system. For many such systems, correct operation is critical to safety, making their security of paramount importance. Unfortunately, because of their heterogeneous nature and special purpose, it is very difficult to determine whether a malicious attacker can make them behave in a manner that causes harm. This type of security analysis is an essential step in building and certifying secure systems.

This poster presents results on a class of load balancing algorithms for large-scale cloud computing systems. We established steady-state perfor-mance of load balancing algorithms in the heavy traffic regime such that the load of system is approaches to one. This is a typical scenario under demand-response. We established a sufficient condition under which the probability that an incoming job is routed to an idle server is one asymp-totically.

Abstract: In this paper, we present two web-based attacks against local IoT devices that any malicious web page or third-party script can perform, even when the devices are behind NATs. In our attack scenario, a victim visits the attacker’s website, which contains a malicious script that communicates with IoT devices on the local network that have open HTTP servers. We show how the malicious script can circumvent the same-origin policy by exploiting error messages on an HTML5 interface or by carrying out DNS rebinding attacks.

Wrist-worn wearable devices provide rich sets of pulsatile physiological data under various modalities and circumstances. An unexploited capability is that the pulsatile physiological time series collected by wrist-worn wearable devices can be used for recovering internal brain dynamics. This Cyber Physical System research project integrates computational algorithms for state-space estimation with wrist-worn wearable devices that sense the physiological signals to present wearable machine-interface architectures related to mental stress.

The goal of the project is to develop techniques that will allow detection and correction of relay misoperations in electric grids. The work from NDSU in (2017-2018): 1) advanced the concept of energy function traces to detect disturbance events in power systems including: temporary and permanent line faults, load loss and excitation failures 2) developed SVD/PCA methods to determine the sensitivity and accuracy of energy-based methods.