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Authors: Shahlaa Mashhadani 1 ; Nathan Clarke 2 and F. Li 3

Affiliations: 1 Centre for Security, Communications and Network Research, Plymouth University, Plymouth, U.K., Computer Science Department, Collage of Education for Pure Science, Ibn Al Haytham, Baghdad and Iraq ; 2 Centre for Security, Communications and Network Research, Plymouth University, Plymouth, U.K., Security Research Institute, Edith Cowan University, Perth, Western Australia and Australia ; 3 School of Computing, University of Portsmouth, Portsmouth and U.K.

ISBN: 978-989-758-359-9

Keyword(s): Digital Forensics, Multimedia Forensics, Automatic Image Annotation, Fusion.

Abstract: With the enormous increase in the use and volume of photographs and videos, multimedia-based digital evidence has come to play an increasingly fundamental role in criminal investigations. However, given the increase in the volume of multimedia data, it is becoming time-consuming and costly for investigators to analyse the images manually. Therefore, a need exists for image analysis and retrieval techniques that are able to process, analyse and retrieve images efficiently and effectively. Outside of forensics, image annotation systems have become increasingly popular for a variety of purposes and major software/IT companies, such as Amazon, Microsoft and Google all have cloud-based image annotation systems. The paper presents a series of experiments that evaluate commercial annotation systems to determine their accuracy and ability to comprehensively annotate images within a forensic image analysis context (rather than simply single object imagery, which is typically the case). The pap er further proposes and demonstrates the value of utilizing a multi-algorithmic approach via fusion to achieve the best results. The results of these experiments show that by existing systems the highest Average Recall was achieved by imagga with 53%, whilst the proposed multi-algorithmic system achieved 77% across the selected datasets. These results demonstrate the benefit of using a multi-algorithmic approach. (More)

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Paper citation in several formats:
Mashhadani, S.; Clarke, N. and Li, F. (2019). Identification and Extraction of Digital Forensic Evidence from Multimedia Data Sources using Multi-algorithmic Fusion.In Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-359-9, pages 438-448. DOI: 10.5220/0007399604380448

@conference{icissp19,
author={Shahlaa Mashhadani. and Nathan Clarke. and F. Li.},
title={Identification and Extraction of Digital Forensic Evidence from Multimedia Data Sources using Multi-algorithmic Fusion},
booktitle={Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2019},
pages={438-448},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007399604380448},
isbn={978-989-758-359-9},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - Identification and Extraction of Digital Forensic Evidence from Multimedia Data Sources using Multi-algorithmic Fusion
SN - 978-989-758-359-9
AU - Mashhadani, S.
AU - Clarke, N.
AU - Li, F.
PY - 2019
SP - 438
EP - 448
DO - 10.5220/0007399604380448

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