@inproceedings{07e0a7c2ee534398bfe9e0e02c1bd649,
title = "SoK: Exploring the state of the art and the future potential of artificial intelligence in digital forensic investigation",
abstract = "Multi-year digital forensic backlogs have become commonplace in law enforcement agencies throughout the globe. Digital forensic investigators are overloaded with the volume of cases requiring their expertise compounded by the volume of data to be processed. Artificial intelligence is often seen as the solution to many big data problems. This paper summarises existing artificial intelligence based tools and approaches in digital forensics. Automated evidence processing leveraging artificial intelligence based techniques shows great promise in expediting the digital forensic analysis process while increasing case processing capacities. For each application of artificial intelligence highlighted, a number of current challenges and future potential impact is discussed.",
keywords = "Deep learning, Digital forensics, Machine learning",
author = "Xiaoyu Du and Chris Hargreaves and John Sheppard and Felix Anda and Asanka Sayakkara and Le-Khac, {Nhien An} and Mark Scanlon",
note = "Publisher Copyright: {\textcopyright} 2020 Owner/Author.; 15th International Conference on Availability, Reliability and Security, ARES 2020 ; Conference date: 25-08-2020 Through 28-08-2020",
year = "2020",
month = aug,
day = "25",
doi = "10.1145/3407023.3407068",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery (ACM)",
booktitle = "Proceedings of the 15th International Conference on Availability, Reliability and Security, ARES 2020",
address = "United States",
}