This work explores the common attributes of different types of cyber risk with a view to better understanding the key attributes that contribute to each type of cyber risk category. In doing so we explore event studies on a range of different market sectors, different countries, different...

Technology is pivotal in the rapid growth of services and intensifying the quality of life. Recent technology, like the Internet of Things (IoT), demonstrates an impressive performance in fast-forward development. Intrusion Detection System (IDS) is used as a lifeline to prevent attacks by...

Serious concerns about the invasion of digital footprint information privacy due to intense commercial promotion through data mining has led to the emergence of privacy by design in the form of the Do Not Track (DNT) mechanism. This paper attempts to construct a theory to justify and find an...

The use of machine learning (ML) methods has been widely discussed for over a decade. The search for the optimal model is still a challenge that researchers seek to address. Despite advances in current work that surpass the limitations of previous ones, research still faces new challenges in...

The problem of forecasting time series is very widely debated. In recent years, machine learning algorithms have been very prolific in this area. This paper describes a systematic approach to building a machine learning predictive model for solving optimization problems in the banking sector. A...

Financial data sets are growing too fast and need to be analyzed. Data science has many different techniques to store and summarize, mining, running simulations and finally analyzing them. Among data science methods, predictive methods play a critical role in analyzing financial data sets. In...