Big data and digital forensics

2016 ◽  
Author(s):  
Oluwasola Mary Adedayo
Keyword(s):  
Big Data ◽  
Digital Forensics

A Study on Digital Forensics in Hadoop

2016 ◽  
Vol 4 (2) ◽  
pp. 473 ◽  
Author(s):  
Sachin Arun Thanekar ◽  
K. Subrahmanyam ◽  
A.B. Bagwan
Keyword(s):  
Big Data ◽  
Open Source ◽  
Data Storage ◽  
High Velocity ◽  
Digital Forensics ◽  
Short Description ◽  
Open Source Tool ◽  
Automated Tool ◽  
Data Forensics

<p>Nowadays we all are surrounded by Big data. The term ‘Big Data’ itself indicates huge volume, high velocity, variety and veracity i.e. uncertainty of data which gave rise to new difficulties and challenges. Hadoop is a framework which can be used for tremendous data storage and faster processing. It is freely available, easy to use and implement. Big data forensic is one of the challenges of big data. For this it is very important to know the internal details of the Hadoop. Different files are generated by Hadoop during its process. Same can be used for forensics. In our paper our focus is on digital forensics and different files generated during different processes. We have given the short description on different files generated in Hadoop. With the help of an open source tool ‘Autopsy’ we demonstrated that how we can perform digital forensics using automated tool and thus big data forensics can be done efficiently.</p>

Digital Investigation of Cybercrimes Based on Big Data Analytics Using Deep Learning

2018 ◽  
pp. 79-101 ◽  
Author(s):  
Ezz El-Din Hemdan ◽  
Manjaiah D. H.
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Data Analytics ◽  
Digital Forensics ◽  
New Technologies ◽  
Early Stage ◽  
Big Data Analytics ◽  
Learning Techniques ◽  
Timely Fashion ◽  
Digital Investigation

Big Data Analytics has become an important paradigm that can help digital investigators to investigate cybercrimes as well as provide solutions to malware and threat prediction, detection and prevention at an early stage. Big Data Analytics techniques can use to analysis enormous amount of generated data from new technologies such as Social Networks, Cloud Computing and Internet of Things to understand the committed crimes in addition to predict the new coming severe attacks and crimes in the future. This chapter introduce principles of Digital Forensics and Big Data as well as exploring Big Data Analytics and Deep Learning benefits and advantages that can help the digital investigators to develop and propose new techniques and methods based on Big Data Analytics using Deep Learning techniques that can be adapted to the unique context of Digital Forensics as well as support performing digital investigation process in forensically sound and timely fashion manner.

scholarly journals On Big Data Forensic - A Case For Forensic Cloud Environment

2020 ◽  
Author(s):  
Oteng Tabona ◽  
Thabiso Maupong ◽  
Kopo Ramokapane ◽  
Thabo Semong ◽  
Banyatsang Mphago
Keyword(s):  
Big Data ◽  
Digital Forensics ◽  
Electronic Devices ◽  
Cloud Environment ◽  
High Rise ◽  
Significant Challenge ◽  
Cyber Crimes ◽  
Definition Of ◽  
Huge Challenge ◽  
Data Forensics

Abstract Background The high rise in electronic devices in modern-day society has resulted in crimes in cyber-related crimes as criminals resort to hacking, illegal use of these devices. This is primarily due to perceived high rewards and low chances of being apprehended. The rise in cyber crimes poses a significant challenge to forensic investigators as now they have to process huge volumes of data from a variety of sources within a limited time. This results in investigators taking longer to process cases and in some instances missing links as they deal with data from a variety of sources. Findings In this paper, we provide a definition of big data forensics, and then we discuss the challenges associated with digital forensics investigations when dealing with big data. We provide details on how volume, variety, and velocity all pose a huge challenge in digital forensics investigations. We then discuss how a novel solution called Forensic Cloud Environment (FCE) leverages the power of Hadoop, HBase, and MapReduce to provide a solution for big data forensic challenges. Conclusion In conclusion, the fact that FCE provides an environment to store huge volumes of data from a variety of sources allows for an improved processing time of data. Hence, providing an environment for big data forensics for the future.

Digital Investigation of Cybercrimes Based on Big Data Analytics Using Deep Learning

2020 ◽  
pp. 615-632 ◽  
Author(s):  
Ezz El-Din Hemdan ◽  
Manjaiah D. H.
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Data Analytics ◽  
Digital Forensics ◽  
New Technologies ◽  
Early Stage ◽  
Big Data Analytics ◽  
Learning Techniques ◽  
Timely Fashion ◽  
Digital Investigation

Big Data Analytics has become an important paradigm that can help digital investigators to investigate cybercrimes as well as provide solutions to malware and threat prediction, detection and prevention at an early stage. Big Data Analytics techniques can use to analysis enormous amount of generated data from new technologies such as Social Networks, Cloud Computing and Internet of Things to understand the committed crimes in addition to predict the new coming severe attacks and crimes in the future. This chapter introduce principles of Digital Forensics and Big Data as well as exploring Big Data Analytics and Deep Learning benefits and advantages that can help the digital investigators to develop and propose new techniques and methods based on Big Data Analytics using Deep Learning techniques that can be adapted to the unique context of Digital Forensics as well as support performing digital investigation process in forensically sound and timely fashion manner.

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