A Review of Evidence Extraction Techniques in Big Data Environment
Today, information era where data is being generated at high in volume, variety, and velocity, a new technology is needed to cope with such data. Companies are no longer depends on the traditional tools and techniques to cater and handle data. Not only ending on how to store and process the data, th...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Conference Paper |
| Language: | English |
| Published: |
2019
|
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Today, information era where data is being generated at high in volume, variety, and velocity, a new technology is needed to cope with such data. Companies are no longer depends on the traditional tools and techniques to cater and handle data. Not only ending on how to store and process the data, they also wanted to gain insight of the data to optimize business process and gain a larger profit. To satisfy these requirements, a good analytic method must be applied to big data in order to extract value and knowledge from these data sets. While computer engineers are working on that part, this valuable data is also being eyed somewhere else. New attacks and attempts to taint the security, privacy, and integrity of the data are being developed somewhere without we knowing. This paper aims to analyze different analytics methods and tools, which can be applied in big data environment, in actionable time while at the same time extract evidence of intrusion in order for the results to be presented in a court of law fitting a digital forensic process. © 2018 IEEE. |
|---|