2,781 research outputs found
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
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
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