Quantitative security metrics are desirable for measuring the performance of information security controls. Security metrics help to make functional and business decisions for improving the performance and cost of the...Quantitative security metrics are desirable for measuring the performance of information security controls. Security metrics help to make functional and business decisions for improving the performance and cost of the security controls. However, defining enterprise-level security metrics has already been listed as one of the hard problems in the Info Sec Research Council's hard problems list. Almost all the efforts in defining absolute security metrics for the enterprise security have not been proved fruitful. At the same time, with the maturity of the security industry, there has been a continuous emphasis from the regulatory bodies on establishing measurable security metrics. This paper addresses this need and proposes a relative security metric model that derives three quantitative security metrics named Attack Resiliency Measure(ARM), Performance Improvement Factor(PIF), and Cost/Benefit Measure(CBM) for measuring the performance of the security controls. For the effectiveness evaluation of the proposed security metrics, we took the secure virtual machine(VM) migration protocol as the target of assessment. The virtual-ization technologies are rapidly changing the landscape of the computing world. Devising security metrics for virtualized environment is even more challenging. As secure virtual machine migration is an evolving area and no standard protocol is available specifically for secure VM migration. This paper took the secure virtual machine migration protocol as the target of assessment and applied the proposed relative security metric model for measuring the Attack Resiliency Measure, Performance Improvement Factor, and Cost/Benefit Measure of the secure VM migration protocol.展开更多
This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic.COVID-19 brings a lot of challenges to government globally.Among the different str...This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic.COVID-19 brings a lot of challenges to government globally.Among the different strategies the most extensively adopted ones were lockdown,social distancing,and isolation among others.Most people with no mental illness history have been found with high risk of distress and psychological discomfort due to anxiety of being infected with the virus.Panic among people due to COVID-19 spread faster than the disease itself.The misinformation and excessive usage of social media in this pandemic era have adversely affected mental health across the world.Due to limited historical data,psychiatrists are finding it difficult to cure the mental illness of people resulting from the pandemic repercussion,fueled by social media forum.In this study the methodology used for data extraction is by considering the implications of social network platforms(such as Reddit)and levering the capabilities of a semi-supervised co-training technique-based use of Naïve Bayes(NB),Random Forest(RF),and Support Vector Machine(SVM)classifiers.The experimental results shows the efficacy of the proposed methodology to identify the mental illness level(such as anxiety,bipolar disorder,depression,PTSD,schizophrenia,and OCD)of those who are in anxious of being infected with this virus.We observed 1 to 5%improvement in the classification decision through the proposed method as compared to state-of-the-art classifiers.展开更多
Context:Since the end of 2019,the COVID-19 pandemic had a worst impact on world’s economy,healthcare,and education.There are several aspects where the impact of COVID-19 could be visualized.Among these,one aspect is ...Context:Since the end of 2019,the COVID-19 pandemic had a worst impact on world’s economy,healthcare,and education.There are several aspects where the impact of COVID-19 could be visualized.Among these,one aspect is the productivity of researcher,which plays a significant role in the success of an organization.Problem:There are several factors that could be aligned with the researcher’s productivity of each domain and whose analysis through researcher’s feedback could be beneficial for decision makers in terms of their decision making and implementation of mitigation plans for the success of an organization.Method:We perform an empirical study to investigate the substantial impact of COVID-19 on the productivity of researchers by analyzing the relevant factors through their perceptions.Our study aims to find out the impact of COVID-19 on the researcher’s productivity that are working in different fields.In this study,we conduct a questionnaire-based analysis,which included feedback of 152 researchers of certain domains.These researchers are currently involved in different research activities.Subsequently,we perform a statistical analysis to analyze the collected responses and report the findings.Findings:The results indicate the substantial impact of COVID-19 pandemics on the researcher’s productivity in terms of mental disturbance,lack of regular meetings,and field visits for the collection of primary data.Conclusion:Finally,it is concluded that researcher’s daily or weekly meetings with their supervisors and colleagues are necessary to keep them more productive in task completion.These findings would help the decision makers of an organization in the settlement of their plan for the success of an organization.展开更多
文摘Quantitative security metrics are desirable for measuring the performance of information security controls. Security metrics help to make functional and business decisions for improving the performance and cost of the security controls. However, defining enterprise-level security metrics has already been listed as one of the hard problems in the Info Sec Research Council's hard problems list. Almost all the efforts in defining absolute security metrics for the enterprise security have not been proved fruitful. At the same time, with the maturity of the security industry, there has been a continuous emphasis from the regulatory bodies on establishing measurable security metrics. This paper addresses this need and proposes a relative security metric model that derives three quantitative security metrics named Attack Resiliency Measure(ARM), Performance Improvement Factor(PIF), and Cost/Benefit Measure(CBM) for measuring the performance of the security controls. For the effectiveness evaluation of the proposed security metrics, we took the secure virtual machine(VM) migration protocol as the target of assessment. The virtual-ization technologies are rapidly changing the landscape of the computing world. Devising security metrics for virtualized environment is even more challenging. As secure virtual machine migration is an evolving area and no standard protocol is available specifically for secure VM migration. This paper took the secure virtual machine migration protocol as the target of assessment and applied the proposed relative security metric model for measuring the Attack Resiliency Measure, Performance Improvement Factor, and Cost/Benefit Measure of the secure VM migration protocol.
文摘This study aims to identify the potential association of mental health and social media forum during the outbreak of COVID-19 pandemic.COVID-19 brings a lot of challenges to government globally.Among the different strategies the most extensively adopted ones were lockdown,social distancing,and isolation among others.Most people with no mental illness history have been found with high risk of distress and psychological discomfort due to anxiety of being infected with the virus.Panic among people due to COVID-19 spread faster than the disease itself.The misinformation and excessive usage of social media in this pandemic era have adversely affected mental health across the world.Due to limited historical data,psychiatrists are finding it difficult to cure the mental illness of people resulting from the pandemic repercussion,fueled by social media forum.In this study the methodology used for data extraction is by considering the implications of social network platforms(such as Reddit)and levering the capabilities of a semi-supervised co-training technique-based use of Naïve Bayes(NB),Random Forest(RF),and Support Vector Machine(SVM)classifiers.The experimental results shows the efficacy of the proposed methodology to identify the mental illness level(such as anxiety,bipolar disorder,depression,PTSD,schizophrenia,and OCD)of those who are in anxious of being infected with this virus.We observed 1 to 5%improvement in the classification decision through the proposed method as compared to state-of-the-art classifiers.
文摘Context:Since the end of 2019,the COVID-19 pandemic had a worst impact on world’s economy,healthcare,and education.There are several aspects where the impact of COVID-19 could be visualized.Among these,one aspect is the productivity of researcher,which plays a significant role in the success of an organization.Problem:There are several factors that could be aligned with the researcher’s productivity of each domain and whose analysis through researcher’s feedback could be beneficial for decision makers in terms of their decision making and implementation of mitigation plans for the success of an organization.Method:We perform an empirical study to investigate the substantial impact of COVID-19 on the productivity of researchers by analyzing the relevant factors through their perceptions.Our study aims to find out the impact of COVID-19 on the researcher’s productivity that are working in different fields.In this study,we conduct a questionnaire-based analysis,which included feedback of 152 researchers of certain domains.These researchers are currently involved in different research activities.Subsequently,we perform a statistical analysis to analyze the collected responses and report the findings.Findings:The results indicate the substantial impact of COVID-19 pandemics on the researcher’s productivity in terms of mental disturbance,lack of regular meetings,and field visits for the collection of primary data.Conclusion:Finally,it is concluded that researcher’s daily or weekly meetings with their supervisors and colleagues are necessary to keep them more productive in task completion.These findings would help the decision makers of an organization in the settlement of their plan for the success of an organization.
