Authors :
Shivjung Adhikari; Yojan Pokhrel
Volume/Issue :
Volume 11 - 2026, Issue 1 - January
Google Scholar :
https://tinyurl.com/3mudtdy3
Scribd :
https://tinyurl.com/mpkzsd4p
DOI :
https://doi.org/10.38124/ijisrt/26jan834
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The role of digital evidence in modern investigations has expanded significantly due to the widespread use of digital
devices and online services. From mobile phones and laptops to cloud platforms and social media, digital traces now form a
central component of criminal, cyber, and civil investigations. However, many investigative agencies, particularly those
operating in lowresource environments, struggle to manage and analyze digital evidence effectively. These challenges arise from
limited access to advanced forensic tools, insufficient technical infrastructure, lack of trained personnel, and increasing
complexity of digital data.
Artificial intelligence (AI) has emerged as a potential supportive technology in digital forensics. AI-based methods can assist
investigators by automating repetitive tasks, sorting large datasets, detecting patterns, and prioritizing potentially relevant
evidence. While AI offers promising benefits, it also introduces technical, ethical, and legal challenges especially in environments
where oversight and resources are limited.
This research paper adopts a narrative and reflective approach to explore the use of AI in digital evidence identification
within low-resource investigative settings. In addition, it reflects on the learning experience gained through participation in this
research under academic supervision. Rather than viewing AI as a replacement for human investigators, the paper positions AI
as a supportive tool that must operate alongside human judgment and ethical responsibility. The study highlights that supervised
research plays a vital role in developing not only technical understanding but also critical thinking, ethical awareness, and
professional maturity among students in cybersecurity and digital forensics.
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The role of digital evidence in modern investigations has expanded significantly due to the widespread use of digital
devices and online services. From mobile phones and laptops to cloud platforms and social media, digital traces now form a
central component of criminal, cyber, and civil investigations. However, many investigative agencies, particularly those
operating in lowresource environments, struggle to manage and analyze digital evidence effectively. These challenges arise from
limited access to advanced forensic tools, insufficient technical infrastructure, lack of trained personnel, and increasing
complexity of digital data.
Artificial intelligence (AI) has emerged as a potential supportive technology in digital forensics. AI-based methods can assist
investigators by automating repetitive tasks, sorting large datasets, detecting patterns, and prioritizing potentially relevant
evidence. While AI offers promising benefits, it also introduces technical, ethical, and legal challenges especially in environments
where oversight and resources are limited.
This research paper adopts a narrative and reflective approach to explore the use of AI in digital evidence identification
within low-resource investigative settings. In addition, it reflects on the learning experience gained through participation in this
research under academic supervision. Rather than viewing AI as a replacement for human investigators, the paper positions AI
as a supportive tool that must operate alongside human judgment and ethical responsibility. The study highlights that supervised
research plays a vital role in developing not only technical understanding but also critical thinking, ethical awareness, and
professional maturity among students in cybersecurity and digital forensics.