Big Data — An evolving concern for forensic investigators

Abstract

Big Data is a term associated with large datasets that come into existence with the volume, velocity and variety of data. An ever increasing human dependence on computers and automated systems has caused data to increase massively. The substantial collection of data is not only helpful for researchers but equally valuable to investigators who intend to carry out forensic analysis of data associated with the criminal cases. The conventional methodologies of performing forensic analysis have changed with the emergence of big data because big data forensic requires more sophisticated tools along with the deployment of efficient frameworks. Up till now several techniques have been devised to help the forensic analysis of small datasets but none of the techniques have been studied by coupling them with big data. Hence in this paper different techniques have been studied by closely analyzing their feasibility in the extraction and the forensic analysis of evidence from large amounts of data. In this paper we discuss various sources of data and how techniques such as the MapReduce framework and phylogenetic trees can help a forensic investigator to visualize large data sets to conduct a forensic analysis. Since audio and video are an attractive source of forensic data therefore this paper also discusses the latest techniques that assist in the extraction of useful sound signals from noise infested audio signals. Similar techniques for forensic analysis of the images have also been presented. Based upon interviews conducted with the forensic professionals, the factors affecting big data forensic techniques along with their severity have been identified so that a scenario specific approach can also be adopted based upon the available investigative resources.