Multi-Layer Cyber-Physical Security and Resilience for Smart Grid

The smart grid is a large-scale complex system that integrates communication technologies with the physical layer operation of the energy systems. Security and resilience mechanisms by design are important to provide guarantee operations for the system. This chapter provides a layered perspective of the smart grid security and discusses game and decision theory as a tool to model the interactions among system components and the interaction between attackers and the system. We discuss game-theoretic applications and challenges in the design of cross-layer robust and resilient controller, secure network routing protocol at the data communication and networking layers, and the challenges of the information security at the management layer of the grid. The chapter will discuss the future directions of using game-theoretic tools in addressing multi-layer security issues in the smart grid.Comment: 16 page

Estimating the location of a Nuclear Source with Multiple Drones in an Urban Environment

The problem of locating the source of radioactive emissions using a network of sensors is considered. Estimating the three-dimensional location of a nuclear source is especially difficult in environments in which no sensor can be placed in close proximity to the source. In this dissertation, maximum-likelihood (ML) estimation is applied to a Poisson process model for radiation received at sensors that is proportional to the inverse square of the distance between the source and the sensor. The joint multivariate density for the sensors is then maximized in order to estimate the location and strength of the radioactive source. Additionally, a limited number of sensors is used to implement a two-stage adaptive algorithm. In the first stage the drones sit at the center of a building\u27s faces and an approximate location of the radiation source is obtained. Based on the results of the first stage, in the second stage the drones move to additional locations to collect more data. The data from both stages is utilized to obtain a more accurate estimate of the location of the radiation source. A third topic involves the effects of spatially non-homogeneous attenuation due to highly absorbing materials such as concrete. A novel metric is presented for identifying situations in which non-homogeneity significantly skews estimation results. This metric is used to drive a multiple iteration multi-stage estimation algorithm utilizing multiple applications of ML estimation. The algorithm is analyzed in realistic situations such as highly absorbing walls and a central shaft. Finally, a hybrid algorithm is proposed that first determines with a high degree of reliability whether non-homogeneous attenuation is present. If non-homogeneous attenuation is declared absent, the sensors move according to the adaptive algorithm. If non-homogeneous attenuation is declared present, the multiple-iteration algorithm is employed. This hybrid algorithm performs extremely well whether non-homogeneous is present or absent

Robust Environmental Mapping by Mobile Sensor Networks

Constructing a spatial map of environmental parameters is a crucial step to preventing hazardous chemical leakages, forest fires, or while estimating a spatially distributed physical quantities such as terrain elevation. Although prior methods can do such mapping tasks efficiently via dispatching a group of autonomous agents, they are unable to ensure satisfactory convergence to the underlying ground truth distribution in a decentralized manner when any of the agents fail. Since the types of agents utilized to perform such mapping are typically inexpensive and prone to failure, this results in poor overall mapping performance in real-world applications, which can in certain cases endanger human safety. This paper presents a Bayesian approach for robust spatial mapping of environmental parameters by deploying a group of mobile robots capable of ad-hoc communication equipped with short-range sensors in the presence of hardware failures. Our approach first utilizes a variant of the Voronoi diagram to partition the region to be mapped into disjoint regions that are each associated with at least one robot. These robots are then deployed in a decentralized manner to maximize the likelihood that at least one robot detects every target in their associated region despite a non-zero probability of failure. A suite of simulation results is presented to demonstrate the effectiveness and robustness of the proposed method when compared to existing techniques.Comment: accepted to icra 201

Quantifying the Resiliency of Fail-Operational Real-Time Networked Control Systems

In time-sensitive, safety-critical systems that must be fail-operational, active replication is commonly used to mitigate transient faults that arise due to electromagnetic interference (EMI). However, designing an effective and well-performing active replication scheme is challenging since replication conflicts with the size, weight, power, and cost constraints of embedded applications. To enable a systematic and rigorous exploration of the resulting tradeoffs, we present an analysis to quantify the resiliency of fail-operational networked control systems against EMI-induced memory corruption, host crashes, and retransmission delays. Since control systems are typically robust to a few failed iterations, e.g., one missed actuation does not crash an inverted pendulum, traditional solutions based on hard real-time assumptions are often too pessimistic. Our analysis reduces this pessimism by modeling a control system\u27s inherent robustness as an (m,k)-firm specification. A case study with an active suspension workload indicates that the analytical bounds closely predict the failure rate estimates obtained through simulation, thereby enabling a meaningful design-space exploration, and also demonstrates the utility of the analysis in identifying non-trivial and non-obvious reliability tradeoffs

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India