Theses supervised by Doç. Dr. Aşkın Demirağ
11 theses · Yeditepe University
Relationship between the parameters of information security risk management process
Due to recorded incidents of Information technology inclined organizations failing to respond effectively to threat incidents, this thesis guideline the benefits of conducting a comprehensive risk assessment which would aid proficiency in responding to potential threats. The ultimate purpose is primarily to identify, quantify and control the key threats that are destructive to achieving business objectives. At the same time, this thesis performs a detailed risk assessment for a case study organization. It contains risk assessment steps, how to apply risk mitigation and effectiveness evaluation after risk assessment in risk management and explains relationship between parameters of the information security risk management processes. The five assets are being defined by organization for risk assessment process. Qualitative analysis techniques are being used to determine possible threats and vulnerabilities in case study. This analysis technique provided clearly determining risk each threat and each asset and vulnerability in organization. As a result of assessment of risk appetite concept, acceptable risks have been defined. It is come out biggest information security risk because of willingly or unwillingly human error as a result of the analysis. All in all, to reduce the impact of risks that is determined as a result of risk assessment has been used efficient control methods that is identified by defense in depth concept.
Collaboration of business intelligence and cloud computing and selecting the best cloud business intelligence solution
In this thesis, business intelligence concept and architecture were explained from data sources to reporting with many advantages provided to institutions in the first part. Then, both cloud computing technology with its service and deployment models and the characteristics of cloud computing experienced clarified in the second part of the thesis. The relationship between cloud computing and business intelligence and the concept arisen from this collaboration, cloud business intelligence, were represented with its benefits and obstacles experienced by companies using this technology in the third part. Four service providers as alternatives serving cloud business intelligence solutions were selected and criteria were determined according to the needs of the company, that would like to use a cloud business intelligence software. After all the criteria are prioritized and the alternatives are determined, the best software was chosen by using the Analytic Hierarchical Process software, called Expert Choice, for decision making.
Analysis and comparison of waterfall model and agile approach in software projects
Looking at the history of civilization from past to present, the concepts of project and project management are frequently encountered. Thanks to project management, businesses can work target-oriented, provide high motivation, facilitate internal control and provide a significant increase in quality. The concept of software, born with the development of technology, penetrates our lives more and more day by day. The globalizing world has brought together the concepts of software and project management and integrated them. Software projects require special management techniques because of their content. For this reason, new methods have emerged over time in the management of software projects. In this study, the concept of the project, the development of project management from its birth over the years, project management in software projects, software development life cycles, and the Waterfall Model and Agile Approach, which are two methods used in software projects, are discussed. The perception of the Waterfall Model and Agile Approach was evaluated with the survey study created with the participation of 145 employees from the software industry. Thus, it is aimed to support managers to choose an effective and efficient method at the point of deciding which method to proceed in software project management.
The effects of using blockchain technology on logistics industry
Today, companies in the logistics sector manage very complex processes for customer satisfaction. One of the most important parts of this complex process is traceability. In today's technology, block chain technology, where data security and traceability meet together, is a golden boon for logistics companies and supply chain. In recent years, information technologies have been used extensively in order to manage complex structures and increase performance in the supply chain. It is predicted that traceability and secure information flow, which are the main features of blockchain technology, can provide a significant benefit to the logistics industry. Almost every logistics company has experienced that they get the return of the right investment they will make here by increasing their information technology resources. Therefore, in this study, the benefit provided by logistics companies investing in blockchain technology has been investigated. As a result of the research, it has been seen that the traceability and secure information flow of blockchain technology benefits all companies investing in this technology. Keywords – Blockchain, Logistic, Blockchain Applications.
Neuromarketing and consumer behavior
In this thesis, the concept of neuromarketing; has been explained in detail, from its relationship with other sciences to the techniques used, from brain physiology to its effect on purchasing behaviors, from its use in advertising to its connection with artificial intelligence. Then, the survey data applied to 409 participants were analyzed using statistical analysis methods in IBM SPSS 22 program to explain the relationship between consumer preferences and behaviors, personality traits, dominant brain region, and demographic features, and their relationships with each other, and the results were analyzed and interpreted. Factor Analysis, Confidence Analysis, Correlation Analysis, T-test, and Chi-Square Analysis were used in the data analysis phase.
The mobile gaming market: The current status and future compared to other gaming platforms
Today, smartphones have become a necessity for everyone. It is used by people of all ages, regardless of whether they are children or the elderly. For this reason, it is more accessible than other gaming platforms. Mobile games have become a platform where people can spend time comfortably while having fun in daily life and it has also become one of the most popular gaming platforms of our time. This thesis contains information about observing events that led to the significant development of mobile games especially cryptocurrency mining, chip crisis and COVID-19. Also, the thesis contains information about how it may follow a path compared to other gaming platforms in order to make a prediction about the improvement of the mobile game industry in the future. The topics mentioned in this thesis will be useful for many people such as game designers, developers and phone manufacturers to produce ideas that are suitable for them. The first part of the thesis provides an in-depth analysis of how the mobile, PC and console platforms led to the emergence of games and how these events happened. The empirical part of the thesis includes the interpretation of the developments of mobile, PC and console platforms over the years with the effect of cryptocurrency mining, chip problem and COVID-19 taking into account the graphics given in the figures. In addition, the empirical part composed of a quantitative questionnaire about to examine and analyze people's attitudes towards mobile games now and in the future. The data analysis was done descriptively. Keywords: Mobile Platform, PC Platform, Console Platform, Game Platforms, Smartphones, Comparison of Gaming Platforms, COVID-19, Chip Crisis, Criptocurrency Mining
Investigation of the impact digital banking transaction performance on customer satisfaction, p.mobile banking sample
The aim of the research is to determine the customer perception and satisfaction level regarding the performance of banking transactions presented in mobile banking applications. The other aim of the study is to reveal the factors that affect customer perception and satisfaction level regarding the performance of banking transactions presented in mobile banking applications. For this aim, a research among 384 random individuals who are over 22 ages, to be attained representing retail banking customers will be organized. The data of the research will be collected online by means of a questionnaire prepared for the purpose. The questionnaire consists of four sections; In the first part, the socio-demographic questionnaire, in the second part, questions to describe the features of the most used mobile banking application, in the third part, questions about the performance of mobile banking transactions, the options used and unused and expected options to be added; There is a Likert type scale for satisfaction level. The remaining survey data are analyzed using statistical analysis methods in IBM SPSS 22 package program. Reliability Analysis, Independent Sample T-Test, ANOVA, Correlation Analysis and Regression Analysis methods are used in the data analysis stage.
Customer churn analysis based on machine learning by using data mining techniques in telecommunication sector
In today's increasingly competitive environment, it is necessary to follow the needs, demands, and expectations of customers closely for the enterprises and to respond in the most appropriate and fastest way. It aims to gain customer loyalty by developing mutual relations with customers and thus to provide long term benefit to the enterprise. Today, the cost of earning new customers is much more than the cost of keeping existing customers. Providing promotions, rebates, gifts or benefits to the customers who are anticipated to churn will be able to hinder the churn customer and thus make more profit in the long term. However, if the wrong prediction is made, this causes unnecessary promotions or gifts to the customer. So for the company, this means a waste of unnecessary money. Therefore, it is important for companies to correctly estimate the churn customer. With the help of technology, enterprises can analyze the data they collect from different sources by using various data mining methods and obtain more valid information about the customers and thus develop more effective communication with customers and ensure their continuity. In this thesis, various data mining techniques and classification algorithms of machine learning were used in order to predict the churn on customer data belonging to the telecommunication company. In the data set, there are 7166 customers' data and there is a flag whether the customer churn or not. Also, 328 customers of the data set have churn label. It aims to estimate churn customers with the highest rate. With the train test split, the data set is divided into 70% - 30% training and test data set. Scale and log transformations are performed on data. The 100 most effective features were selected. The performance of the models obtained by classification algorithms is examined. In this study, customers' data are analyzed with machine learning algorithms by using the Logistic Regression, K Nearest Neighbour (KNN), Naive Bayes, Random Forest, Decision Tree, Support Vector Machine and Gradient Boosting algorithms. K Nearest Neighbour and Random Forest have 0.72 accuracy score that the highest accuracy score among algorithms used. Logistic Regression has 0.65 accuracy score, Support Vector Machine has 0.62 accuracy score, Gradient Boosting has 0.61 accuracy score, Naive Bayes has 0.57 accuracy score and Decision Tree has 0.56 accuracy score.
The art of deception:An analysis of social engineering tacticsin financial fraud
Social engineering is a deceptive tactic used by fraudsters to manipulate individuals into divulging sensitive information or performing actions that are against their best interests. It involves exploiting human psychology and emotions to gain trust and access to confidential information, systems or assets. This paper discusses the different types of social engineering techniques used in fraud, including phishing, pretexting, baiting, and so on. It also examines the impact of social engineering on individuals and the measures that can be taken to prevent or mitigate its effects. By understanding the psychology behind social engineering, individuals can better protect themselves from the negative consequences of these tactics, which can range from identity theft and financial loss to reputational damage and legal liability. Key Words: Fraud, financial fraud, fraud prevention methods, identity theft, social engineering
Digitalisation, new generation technologies and their effects on finance
Technology usage is increasing day by day as development of the technology is increasing. The aim of this thesis is to investigate and identify the present and future effects of digitalisation and financial technologies which are improved by new generation technologies. In addition the term of digitalisation and new generation technologies are presented. These technologies highlight the world-wide competitive game changer effects, but differ from sectoral constructions. The thesis then identifies the uses of financial technologies, and further outlines the structure of financial technologies and services in sectors. In detailed sections of the thesis provide an overview of sectors which are dominated by new generation technologies, including production channel, distribution channel and social and personal channel with well-defined properties. Moreover, detailed sections reveal the statistical calculations, which draws numbers of the cash flow and customer analytics by banking terms according to countries balance sheets and customer reported graphs. Here, comparison of countries is highlighted according to years and terms, and customer reports which answer the big argument of digitalisation. The thesis argues that digitalisation and new generation technologies affect the finance and countries in terms of economic and global conditions in positively. As a result, statistical calculations outline the importance of the digitalisation and new generation technologies on finance. Keywords: Correlation Analysis, Digitalisation, Technology, Finance, Sectoral Technology, Financial Technologies
Fraud detection on remote banking: Unusual behavior on historical pattern and customer profiling
The goal of this thesis is mentioning about history of informatics crimes and fraud on online banking systems. Additionally, I am going to talk about fraud detection systems, the types of these systems and detection models. Banks use specialized software solutions in order to avoid fraud issues as well as other sector companies. Banks's loses are unpredictably higher than the others which means they need to be consistent, determined, fast and smarter than fraudsters. The thesis is going to talk about the architecture of these systems, how data is evaluated internally and how the output is important for banks. Moreover, I will talk about the customer profiling technique that is a machine learning technique which is more precise and makes output easier to handle. Without that technique, all software solutions would be just collection of rules and became just a 'machine'. However, we need a machine that is smarter than a human. Criminals do not follow rules. Why should we?