Digital Forensics Report: Artifactextractor Tool Analysis and Review

This report provides an analysis of Artifactextractor, a digital forensics tool used to extract digital evidence. It begins with an introduction to digital forensics and the role of tools like Artifactextractor in uncovering digital evidence. The report then delves into the tool's background, highlighting its application in sensitive areas such as banking and security for monitoring device activities and investigating data breaches. The solution offered by Artifactextractor is explored, including its ability to capture device activities, solve audit trail issues, and aid in cybersecurity. The report details the tool's code base, emphasizing its use of Python scripting and its ability to extract data from various sources. It also covers the operating system focus, primarily Windows, and the advantages of the tool, such as parallel data extraction and ease of use, as well as its disadvantages, including potential resource waste and automation difficulties. The report also suggests improvements, such as a mobile phone version. Finally, it concludes with recommendations, emphasizing the importance of monitoring and audit in modern business practices and the flexibility of Artifactextractor across different operating systems. References to relevant research papers are also included.

Digital Forensics
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Introduction
Digital forensics offer an opportunity to unveil digital evidence through use of
forensic tools.
Artifactextractor as a tool to discover, analyze and present digital evidence
would be analyzed.
The focus would be on solution offered by the tool, code based platforms,
advantages and its disadvantages.

Background information
Technological advancements have come up with its fair share of challenges and
due to this, monitoring tools are essential.
To monitor device activities, tools such as Artifactextractor have been used in
sensitive industrial areas such as banking and security sectors.
Artifactextractor can be used by organizations to unearth evidential data in
cases of data breaches and privacy issue.
Artifactextractor have proved it a powerful tool to use when investigating data
breaches such as SQL injections.

Artifactextractor problem solution
Artifactextractor captures devices activities as performed by users with aim of
monitoring unwanted user activities.
With use of this tool, it would be possible to solve the issue of lacking audit trail
which can be used make necessary decisions.
To solve the issue of cybersecurity, Artifactextractor can be used to capture logs
from devices which can help in solving cyber crime.
Similarly, parents can make use of Artifactextractor tool to monitor children
activities when given access to computers.

Artifactextractor code base
The tool would make use of python scripting technology.
The extracted data would be dumped from windows and browser as well as
other applications without users knowledge.
The tool can capture data such a all GPS locations the computer has been sued
and extract delete recycle bin data and associate them with specific user.
The developed scripts can be advanced to run on other code based platforms
but python is the core.

Artifactextractor Operating System focus
Artifactextractor can run on different operating systems such as Ubuntu Linux
and Windows.
With understanding that most of computer users use windows, operation of the
tool would be based on Windows OS.
The focus has been necessitated by its ease of use to even non-technical and
considering most organizational employees uses Windows OS.
However, Ubuntu Linux would be used at organizational level to monitor entire
organizational activities.

Advantages of artifcatextractor
It is possible to perform several data extractions in parallel mode through
solvent extraction processes.
Does not require system and tool user to be an expert in technology.
Can extract more than one sample mass of data compared to other available
forensic tools
It is very cheap to acquire as well as use.

Disadvantages of Artifactextractor
Large amount of extractions may result to waste of resources and time.
It is difficult to automate compared to other processes.

Artifactextractor improvement
Technology advancement makes it possible to use mobile phones for business
purposes, this creates need for mobile phones artifcatextractor.
Mobile phones artifactextractor would help organization to monitor all devices
connected to its network.
Additionally, parents would be able to monitor children on use of phones through
use of the tool.
Mobile phones artifcatextractor would make it possible for parents to understand
what children does while online on their own.

Methodology
There are several methods which can be used in data collection and study
processes.
In this case, experimental methodology would be the most appropriate.
Through experimentation, it would be possible for students to have practical
examples on the use of artifactextractor.
The tool can be installed and run from students’ laptops or universities
laboratory.

Conclusions and recommendations
It is evident that monitoring and audit cannot be overlooked as they form
essential part of today’s business.
Artifactextractor has been used by organizations and individuals to monitor
various activities with aim of making informed decisions.
The tool is quite flexible because it can run on Ubuntu Linux and Windows OS.
Artifactextractor can be used in organizations to enforce data privacy and
cybersecurity policies.

References
Harichandran, V. S., Walnycky, D., Baggili, I., & Breitinger, F. 2016. Cufa: A more formal
definition for digital forensic artifacts. Digt Instigatn. 18(1): 125-S137.
Long, C., & Qing, Z.2015. Forensic Analysis of China's Cloud Storage Services. Int J of
Machn Lernig and Comput. 5(6): 467.
Mabuto, E. K., & Venter, H. S. 2012. Analyzing registry, log files, and prefetch files in
finding digital evidence in graphic design applications. The ISC Int J of Info Sec. 4(2):
137-150.
Mohammed, A., & Nwachukwu, E. O. 2015. Computer Forensic: A Reactive Strategy for
Fighting Computer Crime. Int J of Comput Sci and Sec (IJCSS). 9(3): 157.
Mushtaque, K., Ahsan, K., & Umer, A. 2015. Digital forensic investigation models: an
evolution study. JISTEM-J of Info Sytms and Technol Mgnt. 12(2): 233-243.
Panchal, E. P. 2013. Extraction of persistence and volatile forensics evidence from
computer system. Int J Comput Trends Technol (IJCTT). 4(5): 964-968.s