Taking A Look At Digital Forensics

Digital Forensics is a topic that is becoming increasingly important in computing and often requires the intelligent analysis of large amounts of complex data extracted from crime scene. Digital forensics investigation is the process of extracting, analysis digital evidence for use as admissible proof about committed crimes. This process can help to reconstruct the crime events. Big Data analytics (BDA) is a process of analyzing Big Data. The objective of Big Data Analytics is to extract knowledge patterns from massive volume of input data. Recently, there are several challenges led to use Big Data Analytics for digital forensics investigations. Some of these challenges are [14]:
 Storing and backups of large volume of data: traditional data

In order to rapid indexing to analysis of large size of data there is a need to faster methods and devices that have the ability analysis data within a given time frame.
 Presentation and visualization of large amounts of data to the court of law: Presentation and visualization of finding from analysis of digital evidence is an important for presenting the results in a court of law. Presentation and visualization of large of data is a problem faced digital practitioners and examiners in the digital forensics area so that there is a need for new techniques and methods to deal with massive size of data that generated from crime scene in forensically and timely fashion way. Machine learning can considered as an ideal approach to deal with many problems that currently exist in various areas such as multimedia processing, pattern recognition and computer security. Machine learning techniques also can use in digital forensics to solve complex problems in extracting and analysis digital evidence from crime scene. There are several areas in digital forensics where machine learning techniques can be used as

These techniques motivated by digital investigators and examiners to use in the forensic analysis phase. One of recently become popular as extension of machine learning is Deep learning. The Deep Learning algorithms are beneficial when dealing with learning from large amounts of unsupervised data to automatically learn hierarchical representations in deep architectures. The combination of Deep Learning with Big Data Analytics can use for many areas inside digital forensics as