Abstract

Most data, including books, images, photographs, medical records, and even human 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 soft target for different forms of cybercrime as a result of this transition. Digital forensic investigation allows you to retrieve files from a suspect’s laptop that have been accidentally removed or hidden. The available manpower and government resources, however, are insufficient 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 Artificial 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 Traditional DFS techniques are no longer applicable to Digital Forensic (DF) investigators, as they frequently require a DF investigator to manually sift through data in order to locate relevant evidence.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. The main focus of our paper is to conduct a thorough study of the various AI algorithms and their implementation specifically in Digital forensics

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