ABSTRACT
The budding progress and relevance of digital information technology in quite a few areas of business, engineering, medical, agricultural and scientific studies are resulting in data explosion coined by the term “big data”. The dependency on digital media drives and devices has enlarged the dimensions of data formation and storage exponentially around the world, with a need of keeping a record of what data is accumulated and how the data is exercised. So it has raised an alarm of security for the data asset. To discover the pattern of interest leading to a decision from these voluminous data has put forth a challenge for the law enforcement and investigative agencies. Also, tracing such type of misutilization of digital technology in a big data age from the perspective of digital forensics requires minute bit-level examination and observations to locate the digital evidence that explains how maliciously nefarious activities have been done and by whom with the possible extent of the damage. The forensic examination and analysis in such a big data era requires appropriate digital investigation model with the application of tools, techniques and methodologies to boost decision-making and diagnostic process for advanced outfitted competence in digital forensic investigation with the intent of assembling valuable evidence from it. So, the need of the hour is to have a holistic outlook of the big data challenges and opportunities for its application in the digital forensic domain with the goal of making full-bodied investigation pronouncements. Much work has been done to model digital investigation as well as digital evidence but a comprehensive correlated and aggregated merging of voluminous data coming from different heterogeneous sources along with timely and accurate detection and analysis is the need of the hour. This chapter depicts the trends of digital forensics served for big data and the challenges of evidence acquisition, and further suggests the revision of the existing fusion-based digital investigation model by highlighting the formalization, quick detection and timely accurate analysis of digital evidence from multiple sources simultaneously. The modification adopted the inclusion of look-up table into the architecture with the application of data fusion to practice voluminous data effectually.
