Chris Y. T. Ma

Accurate localization of low-level radioactive source under noise and measurement errors

The localization of a radioactive source can be solved in closed-form using 4 ideal sensors and the Apollonius circle in a noise- and error-free environment. When measurement errors and noise such as background radiation are considered, a larger number of sensors is needed to produce accurate results, particularly for extremely low source intensities. In this paper, we present an efficient fusion algorithm that can exploit measurements from n sensors to improve the localization accuracy, and show how the accuracy scales with n. We report testbed results for a 0.911 μCi source to illustrate the effectiveness of our algorithm, in particular performance comparisons with state-of-the-art fusion algorithms based on Mean of Estimates (MoE) and Maximum Likelihood Estimation (MLE). We show that ITP is more accurate than MoE, whereas the choice between ITP and MLE is generally a tradeoff between accuracy and run time efficiency. Higher-intensity radioactive sources are not safe for actual experiments. In this case, we present simulation results based on a validated simulation model. We show that a low-intensity 400 μCi source, similar to the radioactivity of a concealed dirty bomb, can be localized to within 32.5 m using a sensor density of about 1 per 1100 m2 in a surveillance area.

Markov Game Analysis for Attack-Defense of Power Networks Under Possible Misinformation

Electricity grids are critical infrastructures. They are credible targets of active (e.g., terrorist) attacks since their disruption may lead to sizable losses economically and in human lives. It is thus crucial to develop decision support that can guide administrators in deploying defense resources for system security and reliability. Prior work on the defense of critical infrastructures has typically used static or Stackelberg games. These approaches view network interdictions as one-time events. However, infrastructure protection is also a continual process in which the defender and attacker interact to produce dynamic states affecting their best actions, as witnessed in the continual attack and defense of transmission networks in Colombia and Yemen. In this paper, we use zero-sum Markov games to model these interactions subject to underlying uncertainties of real-world events and actions. We solve equilibrium mixed strategies of the players that maximize their respective minimum payoffs with a time-decayed metric. We also show how the defender can use deception as a defense mechanism. Using results for a 5-bus system, a WECC 9-bus system, and an IEEE standard 14-bus system, we illustrate that our game model can provide useful insights. We also contrast our results with those of static games, and quantify the gain in defender payoff due to misinformation of the attacker.

An Experimental Low-Cost, Low-Data-Rate Rapid Structural Assessment Network

In this paper, we present the design, implementation, and experimental evaluation of a wireless sensor network for real-time structural ldquohealthrdquo monitoring. We use simple custom-built gages to detect cracks in critical structural elements. The main data reports require no structural analysis for interpretation, have a low data rate, and are naturally resilient to loss. We show how a variety of low-cost, off-the-shelf data acquisition/communication devices can be used to support remote monitoring by a control center. The heterogeneous hardware is accommodated by the use of open technology standards and a software architecture that is portable, modular, and highly configurable. We present an experimental evaluation of our structural-assessment network done using a full-scale three-story reinforced concrete building that was tested under lateral forces emulating forces induced by earthquakes. Our results show that a set of 12 strategically positioned sensors achieved a 100% detection rate for cracks crossing sensors and a zero false-alarm rate (in the sense that all signals exceeding a preset threshold were traced to cracks exceeding a specified total width).

Proactive fault-tolerant aggregation protocol for privacy-assured smart metering

Smart meters are integral to demand response in emerging smart grids, by reporting the electricity consumption of users to serve application needs. But reporting real-time usage information for individual households raises privacy concerns. Existing techniques to guarantee differential privacy (DP) of smart meter users either are not fault tolerant or achieve (possibly partial) fault tolerance at high communication overheads. In this paper, we propose a fault-tolerant protocol for smart metering that can handle general communication failures while ensuring DP with significantly improved efficiency and lower errors compared with the state of the art. Our protocol handles fail-stop faults proactively by using a novel design of future ciphertexts, and distributes trust among the smart meters by sharing secret keys among them. We prove the DP properties of our protocol and analyze its advantages in fault tolerance, accuracy, and communication efficiency relative to competing techniques. We illustrate our analysis by simulations driven by real-world traces of electricity consumption.

A game theoretic study of attack and defense in cyber-physical systems

Cyber-physical systems encompass a wide range of systems such as sensor networks, cloud computing complexes, and communication networks. They require both the cyber and physical components to function, and hence are susceptible to attacks on either. A cyber-physical system is characterized by the physical space that represents physical components, and the cyber space that represents computations and communications. In this paper, we present a number of game theoretic formulations of attack and defense aspects of cyber-physical systems under different cost and benefit functions and different budgets of the attacker and defender. We discuss the outcomes of the underlying game under linear, negative exponential, and S-shaped benefit functions. We show that the outcomes are determined by the Nash Equilibria (which sometimes occur at budget limits), which in turn determine the system survival.

Quality of monitoring of stochastic events by periodic & proportional-share scheduling of sensor coverage

We analyze the quality of monitoring (QoM) of stochastic events by a periodic sensor which monitors a point of interest (PoI) for q time every p time. We show how the amount of information captured at a PoI is affected by the proportion q/p, the time interval p over which the proportion is achieved, the event type, and the stochastic event arrival dynamics and staying times. The periodic PoI sensor schedule happens in two broad contexts. In the case of static sensors, a sensor monitoring a PoI may be periodically turned off to conserve energy, thereby extending the lifetime of the monitoring until the sensor can be recharged or replaced. In the case of mobile sensors, a sensor may move between the PoIs in a repeating visit schedule. In this case, the PoIs may vary in importance, and the scheduling objective is to distribute the sensors coverage time in proportion to the importance levels of the PoIs. Based on our QoM analysis, we optimize a class of periodic mobile coverage schedules that can achieve such proportional sharing while maximizing the QoM of the total system.

Defense of Cyber Infrastructures Against Cyber-Physical Attacks Using Game-Theoretic Models

The operation of cyber infrastructures relies on both cyber and physical components, which are subject to incidental and intentional degradations of different kinds. Within the context of network and computing infrastructures, we study the strategic interactions between an attacker and a defender using game-theoretic models that take into account both cyber and physical components. The attacker and defender optimize their individual utilities, expressed as sums of cost and system terms. First, we consider a Boolean attack-defense model, wherein the cyber and physical subinfrastructures may be attacked and reinforced as individual units. Second, we consider a component attack-defense model wherein their components may be attacked and defended, and the infrastructure requires minimum numbers of both to function. We show that the Nash equilibrium under uniform costs in both cases is computable in polynomial time, and it provides high-level deterministic conditions for the infrastructure survival. When probabilities of successful attack and defense, and of incidental failures, are incorporated into the models, the results favor the attacker but otherwise remain qualitatively similar. This approach has been motivated and validated by our experiences with UltraScience Net infrastructure, which was built to support high-performance network experiments. The analytical results, however, are more general, and we apply them to simplified models of cloud and high-performance computing infrastructures.

Cloud computing infrastructure robustness: A game theory approach

A cloud computing infrastructure typically consists of a number of sites that house servers and are connected to the Internet. Its operation critically depends both on cyber components, including servers and routers, and physical components, including fiber and power routes. Both types of components are subject to attacks of different kinds and frequencies, which must be accounted for the initial provisioning and subsequent operation of the infrastructure. The cyber and physical components may be individually attacked and defended, and the infrastructure is required to provide an aggregate computational capacity C. We present a game-theoretic approach for the provisioning and operation of the infrastructure under uniform cost models. We first show that the Nash Equilibrium under different formulations to be computable in polynomial time, and derive provisioning choices to ensure the capacity C with probability PS. Then, we derive conditions for reinforcing the infrastructure, and show that higher robustness levels are achieved by limiting the disclosure of information about the infrastructure.

Quality of monitoring of stochastic events by periodic and proportional-share scheduling of sensor coverage

We analyze the quality of monitoring (QoM) of stochastic events by a periodic sensor which monitors a point of interest (PoI) for q time every p time. We show how the amount of information captured at a PoI is affected by the proportion q/p, the time interval p over which the proportion is achieved, the event type in terms of its stochastic arrival dynamics and staying times and the utility function. The periodic PoI sensor schedule happens in two broad contexts. In the case of static sensors, a sensor monitoring a PoI may be periodically turned off to conserve energy, thereby extending the lifetime of the monitoring until the sensor can be recharged or replaced. In the case of mobile sensors, a sensor may move between the PoIs in a repeating visit schedule. In this case, the PoIs may vary in importance, and the scheduling objective is to distribute the sensors coverage time in proportion to the importance levels of the PoIs. Based on our QoM analysis, we optimize a class of periodic mobile coverage schedules that can achieve such proportional sharing while maximizing the QoM of the total system.

Matching and Fairness in Threat-Based Mobile Sensor Coverage

Mobile sensors can be used to effect complete coverage of a surveillance area for a given threat over time, thereby reducing the number of sensors necessary. The surveillance area may have a given threat profile as determined by the kind of threat, and accompanying meteorological, environmental, and human factors. In planning the movement of sensors, areas that are deemed higher threat should receive proportionately higher coverage. We propose a coverage algorithm for mobile sensors to achieve a coverage that will match - over the long term and as quantified by an RMSE metric - a given threat profile. Moreover, the algorithm has the following desirable properties: 1) stochastic, so that it is robust to contingencies and makes it hard for an adversary to anticipate the sensors movement, 2) efficient, and 3) practical, by avoiding movement over inaccessible areas. Further to matching, we argue that a fairness measure of performance over the shorter time scale is also important. We show that the RMSE and fairness are, in general, antagonistic, and argue for the need of a combined measure of performance, which we call efficacy. We show how a pause time parameter of the coverage algorithm can be used to control the trade-off between the RMSE and fairness, and present an efficient offline algorithm to determine the optimal pause time maximizing the efficacy. Finally, we discuss the effects of multiple sensors, under both independent and coordinated operation. Extensive simulation results - under realistic coverage scenarios - are presented for performance evaluation.