2017 IEEE International Conference on Software Quality, Reliability and Security (QRS) 2017
DOI: 10.1109/qrs.2017.29
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A Method for Developing Algorithms for Assessing Cyber-Risk Cost

Abstract: Abstract-We present a method for developing executable algorithms for quantitative cyber-risk assessment. Exploiting techniques from security risk modeling and actuarial approaches, the method pragmatically combines use of available empirical data and expert judgments. The input to the algorithms are indicators providing information about the target of analysis, such as suspicious events observed in the network. Automated execution of the algorithms facilitates continuous assessment.

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Cited by 2 publications
(1 citation statement)
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“…An interesting observation regarding the origin of the data is that each of the primary studies used, on average, more than one data source for deriving their indicators (Figure 10). For example, the approach presented by Erdogan et al [37] reports four data sources as input for cyber-risk assessment (network layer monitoring indicators, application layer monitoring indicators, security test results and business-related information obtained from stakeholders). While we did not record whether these previous studies have shared the datasets openly with others, the benefits of collecting and sharing such data are pointed out by Moore et al [38] and Zheng et al [16].…”
Section: Rq 3: What Is the Origin Of The Data For The Indicators?mentioning
confidence: 99%
“…An interesting observation regarding the origin of the data is that each of the primary studies used, on average, more than one data source for deriving their indicators (Figure 10). For example, the approach presented by Erdogan et al [37] reports four data sources as input for cyber-risk assessment (network layer monitoring indicators, application layer monitoring indicators, security test results and business-related information obtained from stakeholders). While we did not record whether these previous studies have shared the datasets openly with others, the benefits of collecting and sharing such data are pointed out by Moore et al [38] and Zheng et al [16].…”
Section: Rq 3: What Is the Origin Of The Data For The Indicators?mentioning
confidence: 99%