Multicriteria Decision Framework for Cybersecurity Risk Assessment and Management

Risk assessors and managers face many difficult challenges related to novel cyber systems. Among these challenges are the constantly changing nature of cyber systems caused by technical advances, their distribution across the physical, information, and sociocognitive domains, and the complex network structures often including thousands of nodes. Here, we review probabilistic and risk-based decision-making techniques applied to cyber systems and conclude that existing approaches typically do not address all components of the risk assessment triplet (threat, vulnerability, consequence) and lack the ability to integrate across multiple domains of cyber systems to provide guidance for enhancing cybersecurity. We present a decision-analysis-based approach that quantifies threat, vulnerability, and consequences through a set of criteria designed to assess the overall utility of cybersecurity management alternatives. The proposed framework bridges the gap between risk assessment and risk management, allowing an analyst to ensure a structured and transparent process of selecting risk management alternatives. The use of this technique is illustrated for a hypothetical, but realistic, case study exemplifying the process of evaluating and ranking five cybersecurity enhancement strategies. The approach presented does not necessarily eliminate biases and subjectivity necessary for selecting countermeasures, but provides justifiable methods for selecting risk management actions consistent with stakeholder and decisionmaker values and technical data.     

Consistency of the estimator of binary response models based on AUC maximization

This paper examines the asymptotic properties of a binary response model estimator based on maximization of the Area Under receiver operating characteristic Curve (AUC). Given certain assumptions, AUC maximization is a consistent method of binary response model estimation up to normalizations. As AUC is equivalent to Mann-Whitney U statistics and Wilcoxon test of ranks, maximization of area under ROC curve is equivalent to the maximization of corresponding statistics. Compared to parametric methods, such as logit and probit, AUC maximization relaxes assumptions about error distribution, but imposes some restrictions on the distribution of explanatory variables, which can be easily checked, since this information is observable.     

Mobilities

This paper reconstructs the emergence of a student mobilization that occupied a central place in the Mexican political scenario in May and June of 2012. Within the framework of a formally democratic regime with an authoritarian functioning logic, the #YoSoy132 (#IAm132) movement was launched within social networks and quickly became an agent of dissatisfaction with the role played by the media as an interested party in a flawed electoral process. The shift from spontaneous protest to organic mobilization involved extending the proposal beyond the private university to which its first members belonged. It also meant that the initial reactive position gave rise to a collective movement of a proactive nature. Although the future of this movement is still uncertain, spaces for struggle have opened up around it, which have been described as the Mexican Spring.     

Effects of Executive Characteristics and Venture Capital Involvement on Board Composition and Share Ownership in IPO Firms*

Combining the agency perspective, resource‐based view and upper echelon research, this paper examines factors affecting board selection and share ownership in initial public offerings (IPOs). In line with socio‐cognitive and behavioural research, it shows that board independence, cognitive capacity and the incentives of non‐executive directors are negatively associated with the experience and power of executive directors, and that large‐block share ownership is positively associated with the intensity and diversity of non‐executives' experience. However, the retained equity by venture capitalists negatively affects board independence and non‐executive directors' interests. The paper suggests a number of avenues for a future contextual analysis of the board development process in ‘threshold’ firms.     

A scoping review of co-morbidity in individuals with disordered gambling

Individuals with disordered gambling often report at least one other lifetime psychiatric diagnosis. Although prevalence rates vary, there is substantial evidence for co-morbidity being the rule rather than the exception. Despite this known association, there has not been a recent comprehensive review of co-morbidity in disordered gambling other than prevalence surveys. The goal of this study was to broadly summarize and review the current literature on the extent, range and nature of disordered gambling co-morbidity. Following an initial search and screening of 6 databases, 251 articles were included in the final synthesis and evaluation. The main findings showed that few studies examine the mechanisms of co-morbidity in gambling beyond prevalence rates; few studies report on temporal sequencing of gambling and co-morbid disorders; there is a lack of treatment evaluation studies designed specifically for dual-diagnosis individuals; there is a need for system-level initiatives to address co-morbidity at the policy level; and the substance use literature may act as a useful model for guiding future gambling research on co-morbidity. The results suggest that despite a reasonable amount of published research on co-morbidity in disordered gambling, most study conclusions relegate to acknowledgements of high co-occurrence between disorders without follow-up.     

Validating Resilience and Vulnerability Indices in the Context of Natural Disasters

Due to persistent and serious threats from natural disasters around the globe, many have turned to resilience and vulnerability research to guide disaster preparation, recovery, and adaptation decisions. In response, scholars and practitioners have put forth a variety of disaster indices, based on quantifiable metrics, to gauge levels of resilience and vulnerability. However, few indices are empirically validated using observed disaster impacts and, as a result, it is often unclear which index should be preferred for each decision at hand. Thus, we compare and empirically validate five of the top U.S. disaster indices, including three resilience indices and two vulnerability indices. We use observed disaster losses, fatalities, and disaster declarations from the southeastern United States to empirically validate each index. We find that disaster indices, though thoughtfully substantiated by literature and theoretically persuasive, are not all created equal. While four of the five indices perform as predicted in explaining damages, only three explain fatalities and only two explain disaster declarations as expected by theory. These results highlight the need for disaster indices to clearly state index objectives and structure underlying metrics to support validation of the results based on these goals. Further, policymakers should use index results carefully when developing regional policy or investing in resilience and vulnerability improvement projects.     

A Positive False Discovery Rate Convergence Result

The positive false discovery rate (pFDR) is the average proportion of false rejections given that the overall number of rejections is greater than zero. Assuming that the proportion of true null hypotheses, proportion of false positives, and proportion of true positives all converge pointwise, the pFDR converges to a continuous limit uniformly over all significance levels. We are showing that the uniform convergence still holds given a weaker assumption that the proportion of true positives converges in L ¹.