Factors Affecting Automation of Cyber Forensics Investigation - Hayes, Dean (Department of Information Systems, 2024)
Over the past three decades, technology has evolved in a global context changing human interaction through digitization. While there are positive attributes to technological advancement, there are considerable negative elements as well. Cybercrime and digital crime have risen drastically propelling sophisticated digital forensic technology, aimed at fighting cybercrime. However, with automation in digitized Fourth Industrial Revolution, it leaves room to consider the challenges of this on cyber forensic specialists. The purpose of this study was two folded. Firstly, it aimed to identify factors that affect the automation in the cyber forensics investigation. Secondly, it aimed to determine the most important factors in affecting the automation of cyber forensics investigation performance. The research aimed to shed perspective on automation within the lens of cyber forensics, to provide new insights and efficiency regarding cyber forensics processes. It used a positivism research philosophy and quantitative research design. Eleven factors that affect the automation of cyber forensics investigation were identified from literature. Furthermore, eleven hypotheses were generated and were tested using a correlation matrix. Additionally, multiple regression analysis was also used to determine the most important factors that affect the automation of cyber forensics investigation performance. In view of this, the R2 and R2 change were used to determine to what extent the factors influenced the variance in the automation of cyber forensics investigation performance. In this regard, accessibility to data and dependency on Cloud Service Providers (CSPs) were indicated to be the most important factors that had a significant impact on the automation of cyber forensics investigation performance. It was revealed that accessibility to data influence 37.8% of the variation found in the automation of cyber forensics investigation whilst dependency on CSPs was found to influence 17.5% of the variation found in the automation of cyber forensics investigation. On the other hand, the rest of the nine factors each had a combined influence of 1.7% on the variation found in the automation of cyber forensics investigation performance. In light of this, accessibility to data and dependency on CSPs were found to be the most important factors that positively affected the automation of cyber forensics investigation performance. v