Towards Designing a Knowledge Graph-Based Framework for Investigating and Preventing Crime on Online Social Networks
Elezaj, Ogerta; Yildirim Yayilgan, Sule; Kalemi, Edlira; Wendelberg, Linda; Abomhara, Mohamed Ali Saleh; Ahmed, Javed
Journal article, Peer reviewed
Accepted version
Åpne
Permanent lenke
http://hdl.handle.net/11250/2639521Utgivelsesdato
2019Metadata
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Originalversjon
Communications in Computer and Information Science. 2019, 1111 181-195. 10.1007/978-3-030-37545-4_12Sammendrag
Online Social Networks (OSNs) have fundamentally and permanently altered the arena of digital and classical crime. Recently, law enforcement agencies (LEAs) have been using OSNs as a data source to collect Open Source Intelligence for fighting and preventing crime. However, most existing technological developments for LEAs to fight and prevent crime rely on conventional database technology, which poses problems. As social network usage is increasing rapidly, storing and querying data for information retrieval is critical because of the characteristics of social networks, such as unstructured nature, high volumes, velocity, and data interconnectivity. This paper presents a knowledge graph-based framework, an outline of a framework designed to support crime investigators solve and prevent crime, from data collection to inferring digital evidence admissible in court. The main component of the proposed framework is a hybrid ontology linked to a graph database, which provides LEAs with the possibility to process unstructured data and identify hidden patterns and relationships in the interconnected data of OSNs.