Anti-Forensics: Techniques, Challenges and Impact on Digital Forensics

Verified

Added on  2022/08/29

|5
|829
|29
Report
AI Summary
This report provides an overview of anti-forensic techniques, which are methods used to obstruct computer investigations. It discusses various techniques like data hiding, artifact wiping, and trail mystification, along with the challenges they pose to digital forensic professionals. The report highlights the increasing use of these techniques by cybercriminals to evade detection and the need for forensic experts to understand and counter them. It also mentions specific tools like slacker and the importance of staying updated with evolving anti-forensic methods. The conclusion emphasizes the significance of standard workflows and tools in cybercrime investigations while acknowledging the difficulty in identifying those who employ anti-forensics, thus stressing the evolving nature of this field. The report references several research papers and provides a comprehensive understanding of the current state and impact of anti-forensics in digital investigations.
tabler-icon-diamond-filled.svg

Contribute Materials

Your contribution can guide someone’s learning journey. Share your documents today.
Document Page
Running head: ANTI FORENSIC
ANTI FORENSIC
Name of the Student:
Name of the University:
Author’s Note:
tabler-icon-diamond-filled.svg

Secure Best Marks with AI Grader

Need help grading? Try our AI Grader for instant feedback on your assignments.
Document Page
1ANTI FORENSIC
Description:-
It can be a computer analyzer's most horrible nightmare. Computer operators design anti-
forensic apparatuses to create it durable or unbearable to retrieve evidence throughout an
investigation. Anti-forensics denote any procedure, appliance, or software intended to obstruct a
processor investigation. It is also probable to hide a single file inside the other. Executable
information that computers identify as coding languages which are most problematic.
The coding language named packers can pullout executable evidence into other classes of
files, while apparatuses termed binders can fix numerous executable information together (Jain
and Chhabra 2014). Anti-forensic apparatuses, methods, and approaches are becoming a difficult
problem for the digital forensic sector. With the application of anti-forensic methods, it becomes
exhausting to recover information throughout a processor investigation.
Critical Evaluation:-
The internet has a massive number of anti-forensic methods to hide the digital actions of
a singular. Some of these methods are straightforward, whereas some need to complete technical
understanding. The progressive techniques are intentionally applied by the black hat category to
obstruct a cyber-investigation.
Anti-forensics approaches are frequently destroyed into more than a few sub-categories
to create the arrangement of the several tools and methods simpler. Dr. Marcus Rogers
established one of the more extensively acknowledged subcategory failures (Zeng, et al. 2014).
He has projected some sub-categories such as artifact wiping, data hiding, trail mystification, and
attacks besides the computer forensics procedures and apparatuses. Outbreaks against forensics
apparatuses openly have also been titled counter-forensics.
Document Page
2ANTI FORENSIC
Anti-forensics is more than technical expertise. The perception of anti-forensics is neither
innovative nor perfect, but in previous times, forensic scientists have observed a substantial
uptick in the application of anti-forensics (Kim et al. 2017). The most straightforward anti-
forensic apparatuses are also very usual. Safety software like VPN tunneling and encryption help
as details of the illegal hacker's effort once he has penetrated a system.
Anti-forensic apparatuses frequently permit the operator to hide documents within places
like memory, hidden partitions, and slack space. One of the most corporate tools applied is
slacker, part of the Metasploit outline. Slacker permits the operator to divide a file into some
categories, which are then circulated through a structure slack space. Digital forensic researchers
are tackled with new encounters every day as technology advances. Understanding the
procedures digital inquiries follow is maybe one of the most significant characteristics in
learning anti-forensic methods (Fan et al. 2015). Anti-forensics has been approved as a genuine
study field recently. Consequently, it can be measured as an evolving area of attention, and
understanding is deficient in anti-forensics methods.
Conclusion:-
These procedures and implements have become a vital part of an examination of
cybercrimes and gathering digital information in an instance. The forensic experts generally
follow a standard workflow and use well-known approaches and tools while examining a
situation. With the support of recent OS, particularly by the nature of Data management, events,
and evidence, it is easy to discover these individuals. Conversely, due to different procedures
applied by processor users, it is tough to discover persons who apply anti-forensics. The
efficiency of these methods to their operators will also form the measure of this investigation.
Document Page
3ANTI FORENSIC
Problem-statement in the current times, there has been a severe growth in the quantity of anti-
forensic methods used by convicts in unsatisfying investigative procedures.
tabler-icon-diamond-filled.svg

Secure Best Marks with AI Grader

Need help grading? Try our AI Grader for instant feedback on your assignments.
Document Page
4ANTI FORENSIC
References:-
Fan, W., Wang, K., Cayre, F. and Xiong, Z., 2015. Median filtered image quality enhancement
and anti-forensics via variational deconvolution. IEEE transactions on information forensics and
security, 10(5), pp.1076-1091.
Jain, A. and Chhabra, G.S., 2014, August. Anti-forensics techniques: An analytical review. In
2014 Seventh International Conference on Contemporary Computing (IC3) (pp. 412-418). IEEE.
Kim, D., Jang, H.U., Mun, S.M., Choi, S. and Lee, H.K., 2017. Median filtered image restoration
and anti-forensics using adversarial networks. IEEE Signal Processing Letters, 25(2), pp.278-
282.
Zeng, H., Qin, T., Kang, X. and Liu, L., 2014, May. Countering anti-forensics of median
filtering. In 2014 IEEE International Conference on Acoustics, Speech and Signal Processing
(ICASSP) (pp. 2704-2708). IEEE.
chevron_up_icon
1 out of 5
circle_padding
hide_on_mobile
zoom_out_icon
logo.png

Your All-in-One AI-Powered Toolkit for Academic Success.

Available 24*7 on WhatsApp / Email

[object Object]