Muneer Mohammad

Muneer Mohammad

In this paper a new class of cyber attacks against state estimation in the electric power grid is considered. This class of attacks is named false data injection attacks. We show that with the knowledge of the system configuration an attacker could successfully inject false data into certain state variable while bypassing existing techniques for bad data detection. In the preliminary section we consider the feasibility of such an attack and the necessary condition to successfully avoid detection. After that we show that with the knowledge of the system configuration, certain line flow measurements could be manipulated to lead to profitable misconduct. By controlling Regional Transmission Organizations (RTOs) view of system power flow and congestion, an attacker could manipulate the LMPs of targeted buses according to prior biddings. Also, in this paper we show the implementation of the false data injection attacks. The numerical example considered was applied to a malicious data detection algorithm that was designed on a microcontroller. The results demonstrated the effectiveness of injecting false data measurements into the state estimation of electric power grids.

Muneer Mohammad

In this paper an adaptive load management system that uses predictive control optimization is introduced. This price elastic system is able to optimize the consumption of power and is fully autonomous and responsive to market clearing prices. The area of application chosen was an air-conditioning system that allows the end user to select a comfort zone that serves as the boundary conditions for the optimization algorithm. The temperature function that governs our algorithm is also derived and tested. Numerical examples are then presented to show the effectiveness of this system on day-ahead and real-time data from ISOs. The developed system showed promising results and savings that will improve the utilization of present energy resources. Finally, the implementation of this system was discussed and some preliminary modeling was performed to show the potential realization of such a system

Hsien-Pu Chen, Muneer Mohammad, Laszlo B. Kish

The Kirchhoff-law-Johnson-noise (KLJN) scheme is a statistical/physical secure key exchange system based on the laws of classical statistical physics to provide unconditional security. We used the LTSPICE industrial cable and circuit simulator to emulate one of the major active (invasive) attacks, the current injection attack, against the ideal and a practical KLJN system, respectively. We show that two security enhancement techniques, namely, the instantaneous voltage/current comparison method, and a simple privacy amplification scheme, independently and effectively eliminate the information leak and successfully preserve the system's unconditional security.