A Colonel Blotto Game for Interdependence-Aware Cyber-Physical Systems Security in Smart Cities

Smart cities must integrate a number of interdependent cyber-physical systems that operate in a coordinated manner to improve the well-being of the city's residents. A cyber-physical system (CPS) is a system of computational elements controlling physical entities. Large-scale CPSs are more vulnerable to attacks due to the cyber-physical interdependencies that can lead to cascading failures which can have a significant detrimental effect on a city. In this paper, a novel approach is proposed for analyzing the problem of allocating security resources, such as firewalls and anti-malware, over the various cyber components of an interdependent CPS to protect the system against imminent attacks. The problem is formulated as a Colonel Blotto game in which the attacker seeks to allocate its resources to compromise the CPS, while the defender chooses how to distribute its resources to defend against potential attacks. To evaluate the effects of defense and attack, various CPS factors are considered including human-CPS interactions as well as physical and topological characteristics of a CPS such as flow and capacity of interconnections and minimum path algorithms. Results show that, for the case in which the attacker is not aware of the CPS interdependencies, the defender can have a higher payoff, compared to the case in which the attacker has complete information. The results also show that, in the case of more symmetric nodes, due to interdependencies, the defender achieves its highest payoff at the equilibrium compared to the case with independent, asymmetric nodes

Attack-Resilient Minimum Mean-Squared Error Estimation

This work addresses the design of resilient estimators for stochastic systems. To this end, we introduce a minimum mean-squared error resilient (MMSE-R) estimator whose conditional mean squared error from the state remains finitely bounded and is independent of additive measurement attacks. An implementation of the MMSE-R estimator is presented and is shown as the solution of a semidefinite programming problem, which can be implemented efficiently using convex optimization techniques. The MMSE-R strategy is evaluated against other competing strategies representing other estimation approaches in the presence of small and large measurement attacks. The results indicate that the MMSE-R estimator significantly outperforms (in terms of mean-squared error) other realizable resilient (and non-resilient) estimators

D-Separation for Causal Self-Explanation

Rationalization is a self-explaining framework for NLP models. Conventional work typically uses the maximum mutual information (MMI) criterion to find the rationale that is most indicative of the target label. However, this criterion can be influenced by spurious features that correlate with the causal rationale or the target label. Instead of attempting to rectify the issues of the MMI criterion, we propose a novel criterion to uncover the causal rationale, termed the Minimum Conditional Dependence (MCD) criterion, which is grounded on our finding that the non-causal features and the target label are \emph{d-separated} by the causal rationale. By minimizing the dependence between the unselected parts of the input and the target label conditioned on the selected rationale candidate, all the causes of the label are compelled to be selected. In this study, we employ a simple and practical measure of dependence, specifically the KL-divergence, to validate our proposed MCD criterion. Empirically, we demonstrate that MCD improves the F1 score by up to $13.7\%$ compared to previous state-of-the-art MMI-based methods. Our code is available at: \url{https://github.com/jugechengzi/Rationalization-MCD}.Comment: NeurIPS 202

2017 Georgia Southern University Football Coaches and Staff

2017 Coaches and Staf

Psychometric Validation of the BRIEF2 Spanish Version on a Latin Community

Since the early 2000s, the Hispanic population residing in the United States has dramatically grown by 55% (Puente et al., 2015), which increases the importance of understanding how cultural differences may affect neuropsychological test performance. Research demonstrates that pervasive differences exist between the Hispanic community and the dominant culture (Burton et al., 2012). Thus, altering the perception of normative behavior among children (Kärtner et al., 2011). The relative differences in developmental expectations may unfairly disadvantage Hispanic children and potentially lead to the over-pathology of minorities (Burton et al., 2012). The present study aimed to address the potential differences on the BRIEF2 test performances across Spanish-speaking subgroups based on the child’s age and gender, as well as their parents’ country of origin, English proficiency, and education levels. The sample consisted of 41 children (ages 5-18 years) with Spanish-speaking parents residing in the United States. Results suggested that index scores and the global executive composite on the BRIEF2 Spanish Version were significantly impacted by factors including the parents’ English proficiency and education levels, as well as the child’s age. More specifically, parents of children within the 8-12 age group endorsed more difficulties with cognitive regulation and global executive functioning skills than parents with children in the 5-17 and 13-18 age groups. Parents with limited English proficiency were more likely to rate their children with pathological behavioral regulation parents with bilingual or native English proficiency. Fathers with a primary school or graduate school education level were more likely to endorse difficulties with behavioral and cognitive regulation in their children as well as global executive functioning skills, whereas mothers with a middle school education were more likely to endorse difficulties with emotional regulation and global executive functioning skills in their children. The study highlights the need to interpret the results of the BRIEF2 Spanish Version with caution and for continued research with a larger sample size

Game Theory for Secure Critical Interdependent Gas-Power-Water Infrastructure

A city's critical infrastructure such as gas, water, and power systems, are largely interdependent since they share energy, computing, and communication resources. This, in turn, makes it challenging to endow them with fool-proof security solutions. In this paper, a unified model for interdependent gas-power-water infrastructure is presented and the security of this model is studied using a novel game-theoretic framework. In particular, a zero-sum noncooperative game is formulated between a malicious attacker who seeks to simultaneously alter the states of the gas-power-water critical infrastructure to increase the power generation cost and a defender who allocates communication resources over its attack detection filters in local areas to monitor the infrastructure. At the mixed strategy Nash equilibrium of this game, numerical results show that the expected power generation cost deviation is 35\% lower than the one resulting from an equal allocation of resources over the local filters. The results also show that, at equilibrium, the interdependence of the power system on the natural gas and water systems can motivate the attacker to target the states of the water and natural gas systems to change the operational states of the power grid. Conversely, the defender allocates a portion of its resources to the water and natural gas states of the interdependent system to protect the grid from state deviations.Comment: 7 pages, in proceedings of Resilience Week 201

Cities Building Community Wealth

As cities struggle with rising inequality, widespread economic hardship, and racial disparities, something surprising and hopeful is also stirring. In a growing number of America's cities, a more inclusive, community-based approach to economic development is being taken up by a new breed of economic development professionals and mayors. This approach to economic development could be on the cusp of going to scale. It's time it had a name. We call it community wealth building