Intelligent Digital Forensic Analysis Method for CYBER CRIME INVESTIGATION

Abstract

This study aims to provide an intelligent forensic examination and analysis method for large-scale data and data of various resources on diverse cybercrimes that are recently increasing. The purpose of the proposed method is to preemptively cope with cybercrime problems by integrating large amount of data and conducting intelligent analysis of data. A semantic web-based method which performs metadata forensic investigation and analysis, the proposed method consists of four steps: collection, examination, analysis, and presentation. There is an advantage to collecting all metadata of heterogeneous sources from using XML files to represent metadata and then using metadata repository. The Semantic Web technology can integrate metadata in repositories using ontologies to retrieve related metadata. Artificial intelligence and analytical methodologies can be applied to obtain potential evidences that can be used in court in a meaningful way. Because of the increase in cybercrime, the complexity in types of cybercrime, and the limitations of time and resources, it is important to obtain desired outcome in a timely manner in any cybercrime investigation. Instead of the posterior method of chasing a cybercrime after its occurrence, a new method that can preemptively detect and eliminate cybercrime risks is required. The explosive increase of data on cyberspace also calls for efficient forensic techniques for large amount of data. It is expected that this study will ultimately contribute to reducing cybercrimes since proactive detection of and preemptive action against cybercrimes can be accomplished through the use of forensic techniques for large-scale data.