Sebin Gracy

Rice University · Department of Electrical and Computer Engineering

This paper proposes a novel discrete-time multi-virus susceptible-infected-recovered (SIR) model that captures the spread of competing epidemics over a population network. First, we provide sufficient conditions for the infection level of all the viruses over the networked model to converge to zero in exponential time. Second, we propose an observa...

This paper studies the endemic behavior of a multi-competitive networked susceptible-infected-susceptible (SIS) model. Specifically, the paper deals with three competing virus systems (i.e., tri-virus systems). First, we show that a tri-virus system, unlike a bi-virus system, is not a monotone dynamical system. Using the Parametric Transversality T...

We study the spread of multi-competitive viruses over a (possibly) time-varying network of individuals accounting for the presence of shared infrastructure networks that further enables transmission of the virus. We establish a sufficient condition for exponentially fast eradication of a virus for: 1) time-invariant graphs, 2) time-varying graphs w...

In this article, we develop a layered networked spread model for a susceptible-infected-susceptible pathogen-borne disease spreading over a human contact network and an infrastructure network, and refer to it as a layered networked susceptible-infected-water-susceptible model (SIWS). The “W” in SIWS represents any infrastructure network contaminati...

The paper considers continuous-time networked susceptible-infected-susceptible (SIS) diseases spreading over a population. Each agent represents a sub-population and has its own healing rate and infection rate; the state of the agent at a time instant denotes what fraction of the said sub-population is infected with the disease at the said time ins...

This paper studies the endemic behavior of a multi-competitive networked susceptible-infected-susceptible (SIS) model. In particular, we focus on the case where there are three competing viruses (i.e., the tri-virus system). First, we show that the tri-virus system is not a monotone system. Thereafter, we provide a condition that guarantees local e...

The paper deals with the setting where two viruses (say virus~1 and virus~2) coexist in a population, and they are not necessarily mutually exclusive, in the sense that infection due to one virus does not preclude the possibility of simultaneous infection due to the other. We develop a coupled bi-virus susceptible-infected-susceptible (SIS) model f...

In this paper, we analyze the problem of optimally allocating resources in a distributed and privacy-preserving manner. We propose a novel distributed optimal resource allocation algorithm with privacy- preserving guarantees, which operates over a directed communication network. Our algorithm converges in finite time and allows each node to process...

This paper proposes a novel discrete-time multi-virus SIR (susceptible-infected-recovered) model that captures the spread of competing SIR epidemics over a population network. First, we provide a sufficient condition for the infection level of all the viruses over the networked model to converge to zero in exponential time. Second, we propose an ob...

The paper studies the problem of leakage localization in water distribution networks. For the case of a single pipe that suffers from a single leak, by taking recourse to pressure and flow measurements, and assuming those are noiseless, we provide a closed-form expression for leak localization, leak exponent and leak constant. For the aforementione...

This paper proposes a novel discrete-time multi-virus SIR (susceptible-infected-recovered) model that captures the spread of competing SIR epidemics over a population network. First, we provide a sufficient condition for the infection level of all the viruses over the networked model to converge to zero in exponential time. Second, we propose an ob...

The notion of security index quantifies the least effort involved in conducting perfectly undetectable attacks. Thus, the security index enables a systems operator to assess the vulnerability of a component, informs sensor placement strategies, and helps in deciding the feasibility of secure estimators and fault detectors. In this paper, we investi...

We use a deterministic model to study two competing viruses spreading over a two-layer network in the Susceptible--Infected--Susceptible (SIS) framework, and address the central problem of identifying the winning virus in a "survival-of-the-fittest" battle. Existing sufficient conditions ensure that the same virus always wins regardless of initial...

In this paper, we analyze the problem of optimally allocating resources in a distributed and privacy-preserving manner. We focus on the scenario where different cities/entities over a country aim to optimally allocate test kits according to their number of infections for controlling the spread of a pandemic. We propose a distributed privacy-preserv...

This paper deals with the spread of diseases over both a population network and an infrastructure network. We develop a layered networked spread model for a susceptible-infected-susceptible (SIS) pathogen-borne disease spreading over a human contact network and an infrastructure network, and refer to it as a layered networked susceptible-infected-w...

This paper considers the susceptible-infected-susceptible (SIS) epidemic model with an underlying network structure among subpopulations and focuses on the effect of social distancing to regulate the epidemic level. We demonstrate that if each subpopulation is informed of its infection rate and reduces interactions accordingly, the fraction of the...

The paper studies input and state observability (ISO) of discrete-time linear time-invariant network systems whose dynamics are affected by unknown inputs. More precisely, we aim at reconstructing the initial state and the sequence of unknown inputs from the system outputs, and we will use the term ISO when the input reconstruction is possible with...

This paper considers the susceptible-infected-susceptible (SIS) epidemic model with an underlying network structure and focuses on the effect of social distancing to regulate the epidemic level. We demonstrate that if each subpopulation is informed of its infection rate and reduces interactions accordingly, the fraction of the subpopulation infecte...

The paper studies multi-competitive continuous-time epidemic processes in the presence of a shared resource. We consider the setting where multiple viruses are simultaneously prevalent in the population, and the spread occurs due to not only individual-to-individual interaction but also due to individual-to-resource interaction. In such a setting,...

This paper studies epidemic processes over discrete-time periodic time-varying networks. We focus on the susceptible-infected-susceptible (SIS) model that accounts for a (possibly) mutating virus. We say that an agent is in the disease-free state if it is not infected by the virus. Our objective is to devise a control strategy which ensures that al...

In this paper we study a discrete-time SIS (susceptible-infected-susceptible) model, where the infection and healing parameters and the underlying network may change over time. We provide conditions for the model to be well-defined and study its stability. For systems with homogeneous infection rates over symmetric graphs,we provide a sufficient co...

Given a network with the set of vulnerable actuators (and sensors), the security index of an actuator equals the minimum number of sensors and actuators that needs to be compromised so as to conduct a perfectly undetectable attack using the said actuator. This paper deals with the problem of computing actuator security indices for discrete-time LTI...

Actuator security indices are developed for risk assessment purposes. Particularly, these indices can tell a system operator which of the actuators in a critical infrastructure network are the most vulnerable to cyber-attacks. Once the operator has this information, he/she can focus the security budget to protect these actuators. In this short pape...

In this paper, we introduce a continuous-time competing virus model with a shared resource. We say that the system is in the healthy state if all the agents are healthy, and the shared resource is not contaminated. If the epidemic remains persistent, and the shared resource is contaminated, we say that the system is in the endemic state. First of a...

This paper studies epidemic processes over discrete-time periodic time-varying networks. Our objective is to find necessary and sufficient conditions for asymptotic convergence to the disease-free equilibrium (DFE). We provide, in terms of the joint spectral radius of a set of matrices, a sufficient condition for global asymptotic stability (GAS) o...

Motivated by cyber-physical security applications, we face the problem of estimating the state and the input of a linear system, where the input may represent the presence of adversarial attacks. We consider the case where classical filters cannot be used, because the number of measurements is too low, for example it is lower than the size of the i...

This thesis deals with the notion of Input and State Observability (ISO) in linear network systems. One seeks graphical characterizations using the notion of structural (resp. s-structural) ISO. We first focus on linear time-invariant network systems ,represented by fixed graphs, and provide characterizations for strong structural ISO. Thereafter,...

We aim to study the problem of reconstructing the initial state as well as the sequence of unknown inputs (ISO) for linear network systems having time-varying topology. Evolution of such systems can be represented by a collection of graphs {Gk}. We find conditions under which the system with a pattern of fixed zeros imposed by {Gk} is ISO: a)for al...

In this paper, we consider linear network systems with unknown inputs. We present an unbiased recursive algorithm that simultaneously estimates states and inputs. We focus on delay-ℓ left invertible systems with intrinsic delay ℓ ≥ 1, where the input reconstruction is possible only by using outputs up to ℓ time steps later in the future. By showing...

This paper studies linear network systems affected by multiple unknown inputs with the objective of reconstructing both the initial state and the unknown input with one timestep delay. We state conditions under which both the whole network state and the unknown input can be reconstructed from output measurements, over every window of length N, N be...

This paper studies linear time-varying (LTV) network systems affected by multiple unknown inputs. The goal is to reconstruct both the initial state and the unknown input. The main result is a characterization of strong structural input and state observability, i.e., the conditions under which both the whole network state and the unknown input can b...

This paper studies network systems affected by a single unknown input, possibly representing an attack or a failure, to be estimated. The main result is a characterization of input and state observability, namely the conditions under which both the whole network state and the unknown input can be reconstructed from some measured local states. This...