scholarly journals Big Data Forensics: Hadoop 3.2.0 Reconstruction

2020 ◽  
Vol 32 ◽  
pp. 300909
Author(s):  
Edward Harshany ◽  
Ryan Benton ◽  
David Bourrie ◽  
William Glisson
Keyword(s):  
Big Data ◽  
Author(s):  
Thabo Semong ◽  
Thabiso Maupong ◽  
Andrew Blyth ◽  
Oteng Tabona

Author(s):  
Sachin Arun Thanekar ◽  
K. Subrahmanyam ◽  
A.B. Bagwan

<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>


2020 ◽  
Author(s):  
Oteng Tabona ◽  
Thabiso Maupong ◽  
Kopo Ramokapane ◽  
Thabo Semong ◽  
Banyatsang Mphago

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.


Author(s):  
Mohammed Asim ◽  
Dean Richard McKinnel ◽  
Ali Dehghantanha ◽  
Reza M. Parizi ◽  
Mohammad Hammoudeh ◽  
...  

ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  

Find Out About 'Big Data' to Track Outcomes


2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.


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