Energy Sustainability of Turkey in the Case of LNG

Energy is both vital and strategic element for a nation to sustain its fundamental activities like security, logistics, heating, etc. Countries sustain their energy demands through internal or external sources. In the case of not being able to maintain energy demands from their internal sources, they would need to import their requirements. Whenever they need to buy raw materials, they have to build terminals to process the raw material into the required form. The dependency on the imports may cause the importing country to weaken its advantage in international conflicts, unemployment, and welfare. Therefore, countries aim to mitigate dependence to one country and seek for alternate countries. To keep the energy sustainable, they should not be dependent on a sole supplier country. A state chooses to increase its number of providers; it might cause economic advantages or disadvantages regarding the type of material. Besides, particular type of resources requires specific terminals, facilities, and technology to process the material to be ready to consume. Consequently, decision-makers should employ a holistic approach that should comprehend all of the aspects of the situation. We study the case of importing and building a terminal of Liquefied Natural Gas (LNG) to define criteria in maintaining the energy sustainability and profitability of Turkey

Cyber-Assets at Risk (CAR): The Cost of Personally Identifiable Information Data Breaches

Severe financial consequences of data breaches enforce organizations to reconsider their cybersecurity investment. Although attack frequency and trends seem similar per industry, the impact of a data breach may exponentially increase depending on the type of information and the amount of the stolen data. Also, governments develop and improve laws and regulations to protect the privacy of individuals. Therefore, a failure of data security may yield severe penalties and class-action lawsuits, which can significantly increase the expenses than before. The monetary impact of a data breach is a new field of study that requires more sophisticated research and analysis. There are very few studies that quantify the monetary value of data breaches, which are based on the number of affected people or the number of stolen records. This study proposes a new methodology to quantify the monetary value of the data breaches by categorizing information as personally identifiable information (PII) and sensitive personally identifiable information (SPII). Our findings indicate that the categorization of the stolen information has more relation than solely the number of affected people or the number of stolen records. Also, SPII data breaches have more class-action lawsuits, which yield higher costs than PII data breaches

Cybersecurity Acquisition Framework Based on Risk Management: Economics Perspective

Acquisition Research Program Sponsored Report SeriesSponsored Acquisition Research & Technical ReportsCyber attacks continuously target organizations, however, the mitigation actions taken for defense are not sufficiently effective. Ability to compute the cost of attacks is crucial to assess the effectiveness of countermeasure investments. In this study, we developed a framework to have a well-informed decision-making process in cybersecurity acquisition by evaluating the business impact caused by the operability losses of assets. We tested the developed framework using various attack and mitigation scenarios. The findings suggest that using a simulation approach to calculate the business impact of cyber attacks provides the ability to support decision-making process.Approved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

The effects of IL-10 gene polymorphism on serum, and gingival crevicular fluid levels of IL-6 and IL-10 in chronic periodontitis

Objective Anti-inflammatory cytokines play a crucial role in periodontitis by inhibiting synthesis of pro-inflammatory cytokines. The purpose of this study was to evaluate the effect of interleukin-10 (-597) gene polymorphism and genotype distributions on chronic periodontitis (CP) development and IL-6 and IL-10 levels in gingival crevicular fluid (GCF) and serum before and after non-surgical periodontal treatment. Material and Methods The study population consisted of 55 severe generalized CP patients as CP group and 50 healthy individuals as control group. Plaque index, gingival index, probing depth and clinical attachment level were recorded and GCF and blood samples were taken at both the baseline and the sixth week after non-surgical periodontal treatment. PCR-RFLP procedure was used for gene analyses and cytokine levels were measured via ELISA. Results IL-10 genotype distribution was significantly different between CP and control groups (p=0.000, OR:7, 95%CI, 2.83-60.25). Clinical measurements significantly improved in the CP group after periodontal treatment (p;0.05). Sixth week GCF IL-10 levels were significantly lower in patients carrying IL-10 AC+CC genotype compared to the patients carrying IL-10 AA genotype (p;0.05). Conclusion IL-10 AA genotype carriers had lower IL-6 and IL-6/10 levels in serum; however, GCF IL-6/10 levels were similar in both genotypes. Within the limitations of our study, a possible association between IL-10(-597) gene polymorphism and CP might be considered

Crimean-Congo Hemorrhagic Fever Virus in High-Risk Population, Turkey

In the Tokat and Sivas provinces of Turkey, the overall Crimean-Congo hemorrhagic fever virus (CCHFV) seroprevalence was 12.8% among 782 members of a high-risk population. CCHFV seroprevalence was associated with history of tick bite or tick removal from animals, employment in animal husbandry or farming, and being >40 years of age

A Monte-Carlo Analysis of Monetary Impact of Mega Data Breaches

The article of record as published may be found at http://dx.doi.org/10.4018/IJCWT.2021070105The monetary impact of mega data breaches has been a significant concern for enterprises. The study of data breach risk assessment is a necessity for organizations to have effective cybersecurity risk management. Due to the lack of available data, it is not easy to obtain a comprehensive understanding of the interactions among factors that affect the cost of mega data breaches. The Monte Carlo analysis results were used to explicate the interactions among independent variables and emerging patterns in the variation of the total data breach cost. The findings of this study are as follows: The total data breach cost varies significantly with personally identifiable information (PII) and sensitive personally identifiable information (SPII) with unique patterns. Second, SPII must be a separate independent variable. Third, the multilevel factorial interactions between SPII and the other independent variables elucidate subtle patterns in the total data breach cost variation. Fourth, class action lawsuit (CAL) categorical variables regulate the variation in the total data breach cost

Cyber-Assets at Risk (CAR): Monetary Impact of Personally Identifiable Information Data Breaches on Companies

Cyber-systems provide convenience, ubiquity, economic advantage, and higher efficiency to both individuals and organizations. However, vulnerabilities of the cyber domain also offer malicious actors with the opportunities to compromise the most sensitive information. Recent cybersecurity incidents show that a group of hackers can cause a massive data breach, resulting in companies losing competitive advantage, reputation, and money. Governments have since taken some actions in protecting individuals and companies from such crime by authorizing federal agencies and developing regulations. To protect the public from losing their most sensitive records, governments have also been compelling companies to follow cybersecurity regulations. If companies are unsuccessfully protecting their customers\u27 records, they are levied by the government agencies. Companies also may face litigation from individuals after the breach. If the company is a public company, then it must provide more details about the incident. Data breach incidents are one of the significant concerns that organizations have been experiencing for a while. Quantifying the data breach risk into monetary language is a problem that organizations still try to solve due to the unavailability of the data and indirect costs. The cost incurred by personally identifiable information (PII) data breaches may even exceed one billion dollars. Therefore, the monetary cost of a PII data breach is an essential phenomenon that organizations need to forecast and be prepared to mitigate the impact. The purpose of this study is to identify the correlation between the dependent and independent variables and to develop a predictive model to quantify the monetary value of the PII data breaches with multiple regression. This study introduces two new categories for personal information; these are PII and sensitive PII. This new taxonomy accentuates the impact of sensitive information, which is more costly than not sensitive personal information. Next, this study also presents significant results that demonstrate the correlations between revenue, PII, SPII, and class-action lawsuits, and the dependent variable, which is the total cost of the data breach. Also, specific models developed in this study are able to predict the responses for new observations

Economics-Based Risk Management of Distributed Denial of Service Attacks: A Distance Learning Case Study

Managing risk of cyber systems is still on the top of the agendas of Chief Information Security Officers (CISO). Investment in cybersecurity is continuously rising. Efficiency and effectiveness of cybersecurity investments are under scrutiny by boards of the companies. The primary method of decision making on cybersecurity adopts a risk-informed approach. Qualitative methods bring a notion of risk. However, particularly for strategic level decisions, more quantitative methods that can calculate the risk and impact in monetary values are required. In this study, a model is built to calculate the economic value of business interruption during a Distributed Denial-of-Service (DDoS) attack to help decision-makers for selecting the most effective mitigation strategy (ie, acceptance, avoidance, transferal or control). The model is applied to a simulated DDoS attack targeting a distance learning system of a higher education institution. The simulation results show when it is appropriate to accept the risk, buy cyber insurance as a method of risk transfer, or buy DDoS prevention system as a method of risk control