AN OBJECT-BASED MULTIMEDIA FORENSIC ANALYSIS TOOL
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With the enormous increase in the use and volume of photographs and videos, multimedia-based digital evidence now plays an increasingly fundamental role in criminal investigations. However, with the increase, it is becoming time-consuming and costly for investigators to analyse content manually. Within the research community, focus on multimedia content has tended to be on highly specialised scenarios such as tattoo identification, number plate recognition, and child exploitation. An investigator’s ability to search multimedia data based on keywords (an approach that already exists within forensic tools for character-based evidence) could provide a simple and effective approach for identifying relevant imagery. This thesis proposes and demonstrates the value of using a multi-algorithmic approach via fusion to achieve the best image annotation performance. The results show that from existing systems, the highest average recall was achieved by Imagga with 53% while the proposed multi-algorithmic system achieved 77% across the select datasets. Subsequently, a novel Object-based Multimedia Forensic Analysis Tool (OM-FAT) architecture was proposed. The OM-FAT automates the identification and extraction of annotation-based evidence from multimedia content. Besides making multimedia data searchable, the OM-FAT system enables investigators to perform various forensic analyses (search using annotations, metadata, object matching, text similarity and geo-tracking) to help investigators understand the relationship between artefacts, thus reducing the time taken to perform an investigation and the investigator’s cognitive load. It will enable investigators to ask higher-level and more abstract questions of the data, then find answers to the essential questions in the investigation: what, who, why, how, when, and where. The research includes a detailed illustration of the architectural requirements, engines, and complete design of the system workflow, which represents a full case management system. To highlight the ease of use and demonstrate the system’s ability to correlate between multimedia, a prototype was developed. The prototype integrates the functionalities of the OM-FAT tool and demonstrates how the system would help digital investigators find pieces of evidence among a large number of images starting from the acquisition stage and ending in the reporting stage with less effort and in less time.
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