arXiv subjects

Shutian Liu

Publications and source records attributed to Shutian Liu.

At least 19 recordsLinked to original sources

arXiv2026

Bayesian Risk Preference Persuasion

A decision-maker's risk preference is inherently unstable and may adjust in response to external information, shaping subsequent choices and their outcomes. This paper develops a persuasion framework to study how information can be designed to steer risk preferences and decision results. In our framework, a receiver starts with an initial risk preference represented by a coherent risk measure and revises it after observing a system state generated by an information rule claimed by a sender. The revision must preserve time consistency of risk evaluations before and after the state realization. We investigate two models under this framework: one focuses purely on how receiver's risk preference is influenced by information, the other also incorporates receiver's decision. For both models, we investigate the sender's optimal information design problem by analyzing the induced distribution of posterior beliefs over states. Each belief leads to specific preference revisions and corresponding conditional risk assessments. We identify conditions under which information design benefits the sender across several settings and illustrate the framework's potential in risk management through an application to reinsurance design.

math.OC↗

arXiv2026

Games with Incomplete Information Played by Risk-Revising Players

This paper introduces risk-revising players to a class of games with incomplete information. These players enter the game with ex ante risk preferences represented by coherent risk measures and develop time-consistent interim revisions of them contingent on their private information. The standard Nash equilibrium at ex ante stage and Bayesian Nash equilibrium at interim stage are extended to their risk-averse counterparts. Risk-revising Bayesian Nash equilibrium is proposed to capture behavioral outcomes resulting from interim plays based on revised risk preferences. We discuss existence results of these equilibrium concepts. When players' risk revisions correspond to their ex ante equilibrium play, connections are established between equilibria at the ex ante and interim stages. The effect of risk-aversion is analyzed using comparative statics. With the help of the dual representation of risk measures, we illustrate the role of risk-aversion in representing inconsistent beliefs. A numerical example is presented to illustrate the proposed equilibrium concepts under a specific choice of risk preference.

math.OC↗

arXiv2025

Dynamic Information Manipulation Game

We propose a dynamic information manipulation game (DIMG) to investigate the incentives of an information manipulator (IM) to influence the transition rules of a partially observable Markov decision process (POMDP). DIMG is a hierarchical game where the upper-level IM stealthily designs the POMDP's joint state distributions to influence the lower-level controller's actions. DIMG's fundamental feature is characterized by a stagewise constraint that ensures the consistency between the unobservable marginals of the manipulated and the original kernels. In an equilibrium of information distortion, the IM minimizes cumulative cost that depends on the controller's informationally manipulated actions generated by the optimal policy to the POMDP. We discuss ex ante and interim manipulation schemes and show their connections. The effect of manipulation on the performance of control policies is analyzed through its influence on belief distortion.

math.OC↗

arXiv2023

Cyber Insurance for Cyber Resilience

Cyber insurance is a complementary mechanism to further reduce the financial impact on the systems after their effort in defending against cyber attacks and implementing resilience mechanism to maintain the system-level operator even though the attacker is already in the system. This chapter presents a review of the quantitative cyber insurance design framework that takes into account the incentives as well as the perceptual aspects of multiple parties. The design framework builds on the correlation between state-of-the-art attacker vectors and defense mechanisms. In particular, we propose the notion of residual risks to characterize the goal of cyber insurance design. By elaborating the insurer's observations necessary for the modeling of the cyber insurance contract, we make comparison between the design strategies of the insurer under scenarios with different monitoring rules. These distinct but practical scenarios give rise to the concept of the intensity of the moral hazard issue. Using the modern techniques in quantifying the risk preferences of individuals, we link the economic impacts of perception manipulation with moral hazard. With the joint design of cyber insurance design and risk perceptions, cyber resilience can be enhanced under mild assumptions on the monitoring of insurees' actions. Finally, we discuss possible extensions on the cyber insurance design framework to more sophisticated settings and the regulations to strengthen the cyber insurance markets.

cs.CR↗

arXiv2023

Stackelberg Risk Preference Design

Risk measures are commonly used to capture the risk preferences of decision-makers (DMs). The decisions of DMs can be nudged or manipulated when their risk preferences are influenced by factors such as the availability of information about the uncertainties. This work proposes a Stackelberg risk preference design (STRIPE) problem to capture a designer's incentive to influence DMs' risk preferences. STRIPE consists of two levels. In the lower level, individual DMs in a population, known as the followers, respond to uncertainties according to their risk preference types. In the upper level, the leader influences the distribution of the types to induce targeted decisions and steers the follower's preferences to it. Our analysis centers around the solution concept of approximate Stackelberg equilibrium that yields suboptimal behaviors of the players. We show the existence of the approximate Stackelberg equilibrium. The primitive risk perception gap, defined as the Wasserstein distance between the original and the target type distributions, is important in estimating the optimal design cost. We connect the leader's optimality compromise on the cost with her ambiguity tolerance on the follower's approximate solutions leveraging Lipschitzian properties of the lower level solution mapping. To obtain the Stackelberg equilibrium, we reformulate STRIPE into a single-level optimization problem using the spectral representations of law-invariant coherent risk measures. We create a data-driven approach for computation and study its performance guarantees. We apply STRIPE to contract design problems under approximate incentive compatibility. Moreover, we connect STRIPE with meta-learning problems and derive adaptation performance estimates of the meta-parameters.

math.OC↗

arXiv2023

On the Impact of Gaslighting on Partially Observed Stochastic Control

Recent years have witnessed a significant increase in cyber crimes and system failures caused by misinformation. Many of these instances can be classified as gaslighting, which involves manipulating the perceptions of others through the use of information. In this paper, we propose a dynamic game-theoretic framework built on a partially observed stochastic control system to study gaslighting. The decision-maker (DM) in the game only accesses partial observations, and she determines the controls by constructing information states that capture her perceptions of the system. The gaslighter in the game influences the system indirectly by designing the observations to manipulate the DM's perceptions and decisions. We analyze the impact of the gaslighter's efforts using robustness analysis of the information states and optimal value to deviations in the observations. A stealthiness constraint is introduced to restrict the power of the gaslighter and to help him stay undetected. We consider approximate feedback Stackelberg equilibrium as the solution concept and estimate the cost of gaslighting.

math.OC↗

arXiv2022

Distributed Machine Learning with Strategic Network Design: A Game-Theoretic Perspective

This paper considers a game-theoretic framework for distributed machine learning problems over networks where the information acquisition at a node is modeled as a rational choice of a player. In the proposed game, players decide both the learning parameters and the network structure. The Nash equilibrium characterizes the tradeoff between the local performance and the global agreement of the learned classifiers. We first introduce a commutative approach which features a joint learning process that integrates the iterative learning at each node and the network formation. We show that our game is equivalent to a generalized potential game in the setting of undirected networks. We study the convergence of the proposed commutative algorithm, analyze the network structures determined by our game, and show the improvement of the social welfare in comparison with standard distributed learning over fixed networks. To adapt our framework to streaming data, we derive a distributed Kalman filter. A concurrent algorithm based on the online mirror descent algorithm is also introduced for solving for Nash equilibria in a holistic manner. In the case study, we use telemonitoring of Parkinson's disease to corroborate the results.

cs.GT↗

arXiv2022

On the Role of Risk Perceptions in Cyber Insurance Contracts

Risk perceptions are essential in cyber insurance contracts. With the recent surge of information, human risk perceptions are exposed to the influences from both beneficial knowledge and fake news. In this paper, we study the role of the risk perceptions of the insurer and the user in cyber insurance contracts. We formulate the cyber insurance problem into a principal-agent problem where the insurer designs the contract containing a premium payment and a coverage plan. The risk perceptions of the insurer and the user are captured by coherent risk measures. Our framework extends the cyber insurance problem containing a risk-neutral insurer and a possibly risk-averse user, which is often considered in the literature. The explicit characterizations of both the insurer's and the user's risk perceptions allow us to show that cyber insurance has the potential to incentivize the user to invest more on system protection. This possibility to increase cyber security relies on the facts that the insurer is more risk-averse than the user (in a minimization setting) and that the insurer's risk perception is more sensitive to the changes in the user's actions than the user himself. We investigate the properties of feasible contracts in a case study on the insurance of a computer system against ransomware.

cs.CR↗

arXiv2022

Quantum transport in a one-dimensional quasicrystal with mobility edges

Quantum transport in a one-dimensional (1D) quasiperiodic lattice with mobility edges is explored. We first investigate the adiabatic pumping between left and right edge modes by resorting to two edge-bulk-edge channels and demonstrate that the success or failure of the adiabatic pumping depends on whether the corresponding bulk subchannel undergoes a localization-delocalization transition. Compared with the paradigmatic Aubry-André (AA) model, the introduction of mobility edges triggers an opposite outcome for successful pumping in the two channels, showing a discrepancy of critical condition, and facilitates the robustness of the adiabatic pumping against quasidisorder. We also consider the transfer between excitations at both boundaries of the lattice and an anomalous phenomenon characterized by the enhanced quasidisorder contributing to the excitation transfer is found. Furthermore, there exists a parametric regime where a nonreciprocal effect emerges in the presence of mobility edges, which leads to a unidirectional transport for the excitation transfer and enables potential applications in the engineering of quantum diodes.

quant-ph↗

arXiv2022

Mitigating Moral Hazard in Cyber Insurance Using Risk Preference Design

Cyber insurance is a risk-sharing mechanism that can improve cyber-physical systems (CPS) security and resilience. The risk preference of the insured plays an important role in cyber insurance markets. With the advances in information technologies, it can be reshaped through nudging, marketing, or other types of information campaigns. In this paper, we propose a framework of risk preference design for a class of principal-agent cyber insurance problems. It creates an additional dimension of freedom for the insurer for designing incentive-compatible and welfare-maximizing cyber insurance contracts. Furthermore, this approach enables a quantitative approach to reduce the moral hazard that arises from information asymmetry between the insured and the insurer. We characterize the conditions under which the optimal contract is monotone in the outcome. This justifies the feasibility of linear contracts in practice. This work establishes a metric to quantify the intensity of moral hazard and create a theoretic underpinning for controlling moral hazard through risk preference design. We use a linear contract case study to show numerical results and demonstrate its role in strengthening CPS security.

cs.GT↗

arXiv2021

EPROACH: A Population Vaccination Game for Strategic Information Design to Enable Responsible COVID Reopening

The COVID-19 lockdowns have created a significant socioeconomic impact on our society. In this paper, we propose a population vaccination game framework, called EPROACH, to design policies for reopenings that guarantee post-opening public health safety. In our framework, a population of players decides whether to vaccinate or not based on the public and private information they receive. The reopening is captured by the switching of the game state. The insights obtained from our framework include the appropriate vaccination coverage threshold for safe-reopening and information-based methods to incentivize individual vaccination decisions. In particular, our framework bridges the modeling of the strategic behaviors of the populations and the spreading of infectious diseases. This integration enables finding the threshold which guarantees a disease-free epidemic steady state under the population's Nash equilibrium vaccination decisions. The equilibrium vaccination decisions depend on the information received by the agents. It makes the steady-state epidemic severity controllable through information. We find out that the externalities created by reopening lead to the coordination of the rational players in the population and result in a unique Nash equilibrium. We use numerical experiments to corroborate the results and illustrate the design of public information for responsible reopening.

cs.GT↗

arXiv2021

Herd Behaviors in Epidemics: A Dynamics-Coupled Evolutionary Games Approach

The recent COVID-19 pandemic has led to an increasing interest in the modeling and analysis of infectious diseases. The pandemic has made a significant impact on the way we behave and interact in our daily life. The past year has witnessed a strong interplay between human behaviors and epidemic spreading. In this paper, we propose an evolutionary game-theoretic framework to study the coupled evolutions of herd behaviors and epidemics. Our framework extends the classical degree-based mean-field epidemic model over complex networks by coupling it with the evolutionary game dynamics. The statistically equivalent individuals in a population choose their social activity intensities based on the fitness or the payoffs that depend on the state of the epidemics. Meanwhile, the spreading of the infectious disease over the complex network is reciprocally influenced by the players' social activities. We analyze the coupled dynamics by studying the stationary properties of the epidemic for a given herd behavior and the structural properties of the game for a given epidemic process. The decisions of the herd turn out to be strategic substitutes. We formulate an equivalent finite-player game and an equivalent network to represent the interactions among the finite populations. We develop structure-preserving approximation techniques to study time-dependent properties of the joint evolution of the behavioral and epidemic dynamics. The resemblance between the simulated coupled dynamics and the real COVID-19 statistics in the numerical experiments indicates the predictive power of our framework.

cs.GT↗

arXiv2021

Locally-Aware Constrained Games on Networks

Network games have been instrumental in understanding strategic behaviors over networks for applications such as critical infrastructure networks, social networks, and cyber-physical systems. One critical challenge of network games is that the behaviors of the players are constrained by the underlying physical laws or safety rules, and the players may not have complete knowledge of network-wide constraints. To this end, this paper proposes a game framework to study constrained games on networks, where the players are locally aware of the constraints. We use \textit{awareness levels} to capture the scope of the network constraints that players are aware of. We first define and show the existence of generalized Nash equilibria (GNE) of the game, and point out that higher awareness levels of the players would lead to a larger set of GNE solutions. We use necessary and sufficient conditions to characterize the GNE, and propose the concept of the dual game to show that one can convert a locally-aware constrained game into a two-layer unconstrained game problem. We use linear quadratic games as case studies to corroborate the analytical results, and in particular, show the duality between Bertrand games and Cournot games.%, where each layer comprises an unconstrained game.

eess.SY↗

arXiv2020

Dissipation-induced topological phase transition and periodic-driving-induced photonic topological state transfer in a small optomechanical lattice

We propose a scheme to investigate the topological phase transition and the topological state transfer based on the small optomechanical lattice under the realistic parameters regime. We find that the optomechanical lattice can be equivalent to a topologically nontrivial Su-Schrieffer-Heeger (SSH) model via designing the effective optomechanical coupling. Especially, the optomechanical lattice experiences the phase transition between topologically nontrivial SSH phase and topologically trivial SSH phase by controlling the decay of the cavity field and the optomechanical coupling. We stress that the topological phase transition is mainly induced by the decay of the cavity field, which is counter-intuitive since the dissipation is usually detrimental to the system. Also, we investigate the photonic state transfer between the two cavity fields via the topologically protected edge channel based on the small optomechanical lattice. We find that the quantum state transfer assisted by the topological zero energy mode can be achieved via implying the external lasers with the periodical driving amplitudes into the cavity fields. Our scheme provides the fundamental and the insightful explanations toward the mapping of the photonic topological insulator based on the micro-nano optomechanical quantum optical platform.

quant-ph↗

arXiv2020

Photon blockade in a double-cavity optomechanical system with nonreciprocal coupling

Photon blockade is an effective way to generate single photon, which is of great significance in quantum state preparation and quantum information processing. Here we investigate the statistical properties of photons in a double-cavity optomechanical system with nonreciprocal coupling, and explore the photon blockade in the weak and strong coupling regions respectively. To achieve the strong photon blockade, we give the optimal parameter relations under different blockade mechanisms. Moreover, we find that the photon blockades under their respective mechanisms exhibit completely different behaviors with the change of nonreciprocal coupling, and the perfect photon blockade can be achieved without an excessively large optomechanical coupling, i.e., the optomechanical coupling is much smaller than the mechanical frequency, which breaks the traditional cognition. Our proposal provides a feasible and flexible platform for the realization of single-photon source.

quant-ph↗

arXiv2020

Engineering of topological state transfer and topological beam splitter in an even-size Su-Schrieffer-Heeger chain

The usual Su-Schrieffer-Heeger model with an even number of lattice sites possesses two degenerate zero energy modes. The degeneracy of the zero energy modes leads to the mixing between the topological left and right edge states, which makes it difficult to implement the state transfer via topological edge channel. Here, enlightened by the Rice-Male topological pumping, we find that the staggered periodic next-nearest neighbor hoppings can also separate the initial mixed edge states, which ensures the state transfer between topological left and right edge states. Significantly, we construct an unique topological state transfer channel by introducing the staggered periodic on-site potentials and the periodic next-nearest neighbor hoppings added only on the odd sites simultaneously, and find that the state initially prepared at the last site can be transfered to the first two sites with the same probability distribution. This special topological state transfer channel is expected to realize a topological beam splitter, whose function is to make the initial photon at one position appear at two different positions with the same probability. Further, we demonstrate the feasibility of implementing the topological beam splitter based on the circuit quantum electrodynamic lattice. Our scheme opens up a new way for the realization of topological quantum information processing and provides a new path towards the engineering of new type of quantum optical device.

quant-ph↗

arXiv2020

Robust interface-state laser in non-Hermitian micro-resonator arrays

We propose a scheme to achieve the analogous interface-state laser by dint of the interface between the two intermediate-resonator-coupled non-Hermitian resonator chains. We find that, after introducing the couplings between the two resonator chains and the intermediate resonator at the interface, the photons of the system mainly gather into the three resonators near the intermediate resonator. The phenomenon of the photon gathering towards the certain resonators is expected to construct the photon storage and even the laser generator. We reveal that the phenomenon is induced via the joint effect between the isolated intermediate resonator and two kinds of non-Hermitian skin effects. Specially, we investigate the interface-state laser in topologically trivial non-Hermitian resonator array in detail. We find that the pulsed interface-state laser can be achieved accompanying with the intermittent proliferation of the photons at the intermediate resonator when an arbitrary resonator is excited. Also, we reveal that the pulsed interface-state laser in the topologically trivial non-Hermitian resonator array is immune to the on-site defects in some cases, whose mechanism is mainly induced by the nonreciprocal couplings instead of the protection of topology. Our scheme provides a promising and excellent platform to investigate interface-state laser in the micro-resonator array.

quant-ph↗

arXiv2020

Strong mechanical squeezing in a standard optomechanical system by pump modulation

Being beneficial for the amplitude modulation of the pump laser, we propose a simple yet surprisingly effective mechanical squeezing scheme in a standard optomechanical system. By merely introducing a specific kind of periodic modulation into the single-tone driving field to cool down the mechanical Bogoliubov mode, the far beyond 3-dB strong mechanical squeezing can be engineered without requiring any additional techniques. Specifically, we find that the amount of squeezing is not simply dependent on the order of magnitude of the effective optomechanical coupling but strongly on the ratio of sideband strengths for it. To maximize the mechanical squeezing, we numerically and analytically optimize this ratio in the steady-state regime, respectively. The mechanical squeezing engineered in our scheme also has strong robustness and can survive at a high bath temperature. Compared with previous schemes based on the two-tone pump technique, our scheme involves fewer external control laser source and can be extended to other quantum systems to achieve strong squeezing effect.

quant-ph↗