1,721,064 research outputs found
An Overview of Security Breach Probability Models
No full textCybersecurity breach probability functions describe how cybersecurity investments impact the actual vulnerability to cyberattacks through the probability of success of the attack. They essentially use mathematical models to make cyber-risk management choices. This paper provides an overview of the breach probability models that appear in the literature. For each of them, the form of the mathematical functions and their properties are described. The models exhibit a wide variety of functional relationships between breach probability and investments, including linear, concave, convex, and a mixture of the latter two. Each model describes a parametric family, with some models have a single parameter, and others have two. A sensitivity analysis completes the overview to identify the impact of the model parameters: the estimation of the parameters which have a larger influence on the breach probability is more critical and deserves greater attention
Robustness of Optimal Investment Decisions in Mixed Insurance/Investment Cyber Risk Management
No full textAn integrated risk management strategy, combining insurance and security investments, where the latter contribute to reduce the insurance premium, is investigated to assess whether it can lead to reduced overall security expenses. The optimal investment for this mixed strategy is derived under three insurance policies, covering, respectively, all the losses (total coverage), just those below the limit of maximum liability (partial coverage), and those above a threshold but below the maximum liability (partial coverage with deductibles). Under certain conditions (e.g., low potential loss, or either very low or very high vulnerability), the mixed strategy reverts however to insurance alone, because investments do not provide an additional benefit. When the mixed strategy is the best choice, the dominant component in the overall security expenses is the insurance premium in most cases. Optimal investment decisions require an accurate estimate of the vulnerability, whereas larger estimation errors may be tolerated for the investment-effectiveness coefficient
Pricing Cat Bonds for Cloud Service Failures
No full textThe use of the cloud to store personal/company data and to run programs is gaining wide acceptance as it is more efficient and cost-effective. However, cloud services may not always be available, which could lead to losses for customers and the cloud provider (the provider is typically obligated to compensate its customers). It can protect itself from such losses through insurance, which transfers the risk to the insurer. In the case of poor cloud availability, the amount that the insurer has to pay back to the cloud provider may become so high that it endangers the insurer’s financial solvency. We propose the use of cat bonds as reinsurance tools as well as the Nowak–Romaniuk pricing scheme. The outage frequency was described by the Poisson process and the loss severity was described by a Pareto random variable; we derived a closed formula for the price of a cat bond in a stochastic interest rate environment, using both one-factor and two-factor short-rate models. We demonstrated the applicability of our pricing formula in a real context
Cyber Insurance Premium Setting for Multi-Site Companies under Risk Correlation
No full textCorrelation in cyber risk represents an additional source of concern for utility and industrial infrastructures, where risks may be introduced by connected systems. A major means of reducing risk is to transfer it through insurance. In this paper, we consider a company which has peripheral branches in addition to its headquarters, where risk correlation is present between all of its sites and insurance is adopted to hedge against economic losses. We employ the expected utility principle (which leads to the well-known mean variance premium formula) to derive the insurance premium under risk correlation under several risk scenarios. Under a first-order approximation, a quasi-linear relationship between the premium and the two major risk factors (the number of branches and the risk correlation coefficient) is determined
Predicting the performance of TV series through textual and network analysis: The case of Big Bang Theory
No full textTV series represent a growing sector of the entertainment industry. Being able to predict their performance allows a broadcasting network to better focus the high investment needed for their preparation. In this paper, we consider a well known TV series—The Big Bang Theory—to identify factors leading to its success. The factors considered are mostly related to the script, such as the characteristics of dialogues (e.g., length, language complexity, sentiment), while the performance is measured by the reviews submitted by viewers (namely the number of reviews as a measure of popularity and the viewers’ ratings as a measure of appreciation). Through correlation and regression analysis, two sets of predictors are identified respectively for appreciation and popularity. In particular the episode number, the percentage of male viewers, the language complexity and text length emerge as the best predictors for popularity, while again the percentage of male viewers and the language complexity plus the number of we-words and the concentration of dialogues are the best choice for appreciation.</div
Traffic Modellind and Statistical Analysis in Network Tomography
No full textThe estimation of traffic matrices in a communications network on the basis of multiperiod traffic measurements on network links is an important problem, and several solutions have been proposed when the traffic does not show dependence over time. However, extensive measurements campaigns conducted on IP networks have shown that the traffic actually exhibits long range dependence. Here a method is proposed for the estimation of traffic matrices in the case of long range dependence, and its properties are studied
Concentration Indices for Dialogue Dominance Phenomena in TV Series: The Case of the Big Bang Theory
No full textDialogues in a TV series (especially in sitcoms) represent the main interaction among characters. Dialogues may exhibit concentration, with some characters dominating, or showing instead a choral action, where all characters contribute equally to the conversation. The degree of concentration represents a distinctive feature (a signature) of the TV series. In this paper, we advocate the use of a concentration index (the Hirschman–Herfindahl Index) to examine dominance phenomena in TV series and apply it to the Big Bang Theory TV series. The use of the concentration index allows us to reveal a declining trend in dialogue concentration as well as the decline of some characters and the emergence of others. We find the decline in dominance to be highly correlated with a decline in popularity. A stronger concentration is present for episodes (i.e. by analysing concentration of episodes rather than speaking lines), where the number of characters that dominate episodes is quite small
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