Most data, including books, images, photographs, medical records, and even hu man genetic material, has moved to digital formats in recent years. Laptops, -
smartphones, and connected devices are the primary sources of this digital data transformation, and they are quickly becoming an integral part of our everyday lives. We
are becoming a sof target for different forms of cybercrime as a result of this transition. Digital forensic investigation allows you to retrieve fles from a suspect’s laptop
that have been accidentally removed or hidden. Te available manpower and government resources, however, are insufcient to investigate cybercrime. Unfortunately,
current automated forensic protocols and practices necessitate a lot of human contact,
which slows down the process and slows down the rate at which digital crimes are
committed. Over the last few years, the use of Artifcial Intelligence (AI) in Digital
Forensic Science (DFS) approaches to cybercrime investigations has gotten a lot of
attention. Traditional DFS techniques are no longer applicable to Digital Forensic (DF)
investigators, as they frequently require a DF investigator to manually sif through data
in order to locate relevant evidence. In order for Digital Forensic Science to keep up
with the demands, which are compounded by Big Data, more intelligent Digital Forensic investigation techniques are needed. Te main focus of our paper is to conduct
a thorough study of the various AI algorithms and their implementation specifcally in
Digital forensics