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New Approach of Artificial Intelligence in Digital Forensic Investigation: A Literature Review

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Proceedings of ICACTCE'23 — The International Conference on Advances in Communication Technology and Computer Engineering (ICACTCE 2023)

Abstract

A Digital Forensic is a subfield of forensic science known as “digital forensic science” that focuses on the recovery and examination of data from digital devices that are connected to cybercrime. Computer forensics was the original meaning of the word “digital forensics.” it has broadened to include any device that could store digital data. National policies on digital forensics didn't start to arise until the beginning of the twenty-first century. The process of locating, protecting, analyzing, and documenting digital evidence is known as digital forensics. When necessary, this is done so that evidence can be presented in court. AI in Digital forensics is one of the technologies that is developing the fastest, and it has had a significant impact on the methods and tools used to examine, monitor, and visualize crime scenes as well as develop effective strategies for dealing with impending threats and attacks on the internet and cyberspace. Modern technology has replaced human labor with machine-oriented designed work that has the capability and ability to minimize error and increase quality, reducing human effort and achieving maximum results with the fewest possible errors. It can influence the outcome and analyze the evidence in the field of digital forensics in a more effective manner to track the outcomes.

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Acknowledgements

“This work was supported by the Slovak Research and Development Agency under the contract No. APVV-19-0581”.

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Correspondence to Karan Kumar .

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Verma, R. et al. (2023). New Approach of Artificial Intelligence in Digital Forensic Investigation: A Literature Review. In: Iwendi, C., Boulouard, Z., Kryvinska, N. (eds) Proceedings of ICACTCE'23 — The International Conference on Advances in Communication Technology and Computer Engineering. ICACTCE 2023. Lecture Notes in Networks and Systems, vol 735. Springer, Cham. https://doi.org/10.1007/978-3-031-37164-6_30

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