The Experts below are selected from a list of 17244 Experts worldwide ranked by ideXlab platform
José Luis Rivas López - One of the best experts on this subject based on the ideXlab platform.
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Improving information security risk analysis by including Threat-Occurrence predictive models
Computers & Security, 2020Co-Authors: Pedro Tubío Figueira, Cristina López Bravo, José Luis Rivas LópezAbstract:Abstract Protecting information is a crucial issue in today society, in both work and home environments. Over the years, different tools and technologies have contributed to safeguarding information, including risk analysis methodologies developed to evaluate the risk of Threat materialization despite security measures. Traditional risk analysis methodologies base risk computation on, among other parameters, the frequency of Occurrence of Threats, which is gathered from available historical data. However, as new safeguards are implemented, and vulnerability potential changes, Threat frequencies may also change. To take into account the current state of an organization’s system as well as historical data, we propose to substitute past Threat frequency by the probability of a Threat occurring in the future. To compute this future Threat probability, we use regression models, validated by a risk analysis for a Spanish SME based on Magerit (Spanish adaptation of ISO/IEC 27005). The results show that the future probability of each Threat can be calculated with accuracy, precision, sensitivity and specificity rates above 70%. Obtaining a more realistic risk estimate (reflecting to the current state of vulnerabilities) is translated into the adoption of better and more efficient safeguards that reduce losses and improve information security in a business.
Joseph J. James - One of the best experts on this subject based on the ideXlab platform.
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People's thresholds of decision-making against a tornado Threat using dynamic probabilistic hazard information
International Journal of Disaster Risk Reduction, 2020Co-Authors: Seyed M. Miran, Chen Ling, Joseph J. JamesAbstract:Abstract With pervasive use of smartphones for acquiring weather information and efforts of National Oceanic and Atmospheric Administration (NOAA) in developing a tool under the banner of the Forecasting a Continuum of Environmental Threats (FACETs) to disseminate probabilistic information about a tornado event, it is important to investigate people's probabilistic thresholds for taking protective action when presented with dynamic visual information about a tornado Threat on a smartphone. We presented dynamic displays of probabilistic information of five hypothetical tornado scenarios to 109 college students on their smartphones and asked them to report at what moment they would take protective action (if any). After conducting Cox proportional hazard regression and Poisson regression, we found that proximity to the tornado, likelihood of the Threat Occurrence, and being inside vs. outside of the risk area played a significant role in people's decision-making. This study illustrated that regardless of tornado trajectory, as a moving probabilistic swath showing probabilistic forecast of the tornado becomes closer to the information recipients, around 12% of the participants would take protective action prior to being impacted by the probabilistic zone with more than 0% chance of the tornado Occurrence. Almost half of them would take protective action before being impacted by the probabilistic zone with more than 20% chance, and around 88% of the participants would take protective action before being impacted by the probabilistic zone with more than 40% chance of the tornado Occurrence. Our study corroborates previous relevant research that providing probabilistic hazard information to the public could enhance the warnings' effectiveness.
Seyed M. Miran - One of the best experts on this subject based on the ideXlab platform.
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People's thresholds of decision-making against a tornado Threat using dynamic probabilistic hazard information
International Journal of Disaster Risk Reduction, 2020Co-Authors: Seyed M. Miran, Chen Ling, Joseph J. JamesAbstract:Abstract With pervasive use of smartphones for acquiring weather information and efforts of National Oceanic and Atmospheric Administration (NOAA) in developing a tool under the banner of the Forecasting a Continuum of Environmental Threats (FACETs) to disseminate probabilistic information about a tornado event, it is important to investigate people's probabilistic thresholds for taking protective action when presented with dynamic visual information about a tornado Threat on a smartphone. We presented dynamic displays of probabilistic information of five hypothetical tornado scenarios to 109 college students on their smartphones and asked them to report at what moment they would take protective action (if any). After conducting Cox proportional hazard regression and Poisson regression, we found that proximity to the tornado, likelihood of the Threat Occurrence, and being inside vs. outside of the risk area played a significant role in people's decision-making. This study illustrated that regardless of tornado trajectory, as a moving probabilistic swath showing probabilistic forecast of the tornado becomes closer to the information recipients, around 12% of the participants would take protective action prior to being impacted by the probabilistic zone with more than 0% chance of the tornado Occurrence. Almost half of them would take protective action before being impacted by the probabilistic zone with more than 20% chance, and around 88% of the participants would take protective action before being impacted by the probabilistic zone with more than 40% chance of the tornado Occurrence. Our study corroborates previous relevant research that providing probabilistic hazard information to the public could enhance the warnings' effectiveness.
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The effect of providing probabilistic information about a tornado Threat on people’s protective actions
Natural Hazards, 2018Co-Authors: Seyed M. Miran, Chen Ling, Alan Gerard, Lans RothfuszAbstract:National Weather Service issues deterministic warnings in a tornado event. An alternative system is being researched at National Severe Storms Laboratory to issue Probabilistic Hazard Information (PHI). This study investigated how providing the uncertainty information about the tornado Occurrence through PHI changes people’s protective actions. In an experiment, visual displays of the probabilistic information and deterministic warnings were presented to fifty participants to report their expected protective actions in different scenarios. It was found that the percentage of people who expected to immediately take shelter right after receiving the weather information increased exponentially as their proximity to the Threat decreased. When there was more chance that the information about Occurrence of a particular tornado was false rather than true, in scenarios that the likelihood of the Threat Occurrence was less than 50%, providing it through PHI lowered the percentage of people who immediately took shelter. The ordinal logistic regression models showed that the probability of taking protective actions significantly changes by providing the uncertainty information when people have less than 20 min lead time before getting impacted by the Threat. When the lead time is less than 10 min, the probability of immediately taking shelter increases to 94 from 71%, and when the lead time is more than 10 but less than 20 min, that probability increases from 53 to 70%, if they are provided with the probabilistic information. Presenting the likelihood of any tornado formation in the area did not have significant effect on the people’s protective actions.
Pedro Tubío Figueira - One of the best experts on this subject based on the ideXlab platform.
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Improving information security risk analysis by including Threat-Occurrence predictive models
Computers & Security, 2020Co-Authors: Pedro Tubío Figueira, Cristina López Bravo, José Luis Rivas LópezAbstract:Abstract Protecting information is a crucial issue in today society, in both work and home environments. Over the years, different tools and technologies have contributed to safeguarding information, including risk analysis methodologies developed to evaluate the risk of Threat materialization despite security measures. Traditional risk analysis methodologies base risk computation on, among other parameters, the frequency of Occurrence of Threats, which is gathered from available historical data. However, as new safeguards are implemented, and vulnerability potential changes, Threat frequencies may also change. To take into account the current state of an organization’s system as well as historical data, we propose to substitute past Threat frequency by the probability of a Threat occurring in the future. To compute this future Threat probability, we use regression models, validated by a risk analysis for a Spanish SME based on Magerit (Spanish adaptation of ISO/IEC 27005). The results show that the future probability of each Threat can be calculated with accuracy, precision, sensitivity and specificity rates above 70%. Obtaining a more realistic risk estimate (reflecting to the current state of vulnerabilities) is translated into the adoption of better and more efficient safeguards that reduce losses and improve information security in a business.
Chen Ling - One of the best experts on this subject based on the ideXlab platform.
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People's thresholds of decision-making against a tornado Threat using dynamic probabilistic hazard information
International Journal of Disaster Risk Reduction, 2020Co-Authors: Seyed M. Miran, Chen Ling, Joseph J. JamesAbstract:Abstract With pervasive use of smartphones for acquiring weather information and efforts of National Oceanic and Atmospheric Administration (NOAA) in developing a tool under the banner of the Forecasting a Continuum of Environmental Threats (FACETs) to disseminate probabilistic information about a tornado event, it is important to investigate people's probabilistic thresholds for taking protective action when presented with dynamic visual information about a tornado Threat on a smartphone. We presented dynamic displays of probabilistic information of five hypothetical tornado scenarios to 109 college students on their smartphones and asked them to report at what moment they would take protective action (if any). After conducting Cox proportional hazard regression and Poisson regression, we found that proximity to the tornado, likelihood of the Threat Occurrence, and being inside vs. outside of the risk area played a significant role in people's decision-making. This study illustrated that regardless of tornado trajectory, as a moving probabilistic swath showing probabilistic forecast of the tornado becomes closer to the information recipients, around 12% of the participants would take protective action prior to being impacted by the probabilistic zone with more than 0% chance of the tornado Occurrence. Almost half of them would take protective action before being impacted by the probabilistic zone with more than 20% chance, and around 88% of the participants would take protective action before being impacted by the probabilistic zone with more than 40% chance of the tornado Occurrence. Our study corroborates previous relevant research that providing probabilistic hazard information to the public could enhance the warnings' effectiveness.
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The effect of providing probabilistic information about a tornado Threat on people’s protective actions
Natural Hazards, 2018Co-Authors: Seyed M. Miran, Chen Ling, Alan Gerard, Lans RothfuszAbstract:National Weather Service issues deterministic warnings in a tornado event. An alternative system is being researched at National Severe Storms Laboratory to issue Probabilistic Hazard Information (PHI). This study investigated how providing the uncertainty information about the tornado Occurrence through PHI changes people’s protective actions. In an experiment, visual displays of the probabilistic information and deterministic warnings were presented to fifty participants to report their expected protective actions in different scenarios. It was found that the percentage of people who expected to immediately take shelter right after receiving the weather information increased exponentially as their proximity to the Threat decreased. When there was more chance that the information about Occurrence of a particular tornado was false rather than true, in scenarios that the likelihood of the Threat Occurrence was less than 50%, providing it through PHI lowered the percentage of people who immediately took shelter. The ordinal logistic regression models showed that the probability of taking protective actions significantly changes by providing the uncertainty information when people have less than 20 min lead time before getting impacted by the Threat. When the lead time is less than 10 min, the probability of immediately taking shelter increases to 94 from 71%, and when the lead time is more than 10 but less than 20 min, that probability increases from 53 to 70%, if they are provided with the probabilistic information. Presenting the likelihood of any tornado formation in the area did not have significant effect on the people’s protective actions.