Crime Prevention, Detection and Investigation Using Digital Evidence and Artificial Intelligence

Dear Colleagues,

There are numerous social networks such as Facebook, LinkedIn, Google Plus and Twitter and an abundance of valuable information in the form of chat text, images, videos, networking graphs of individuals, etc., which can be used to prevent, detect and solve crimes. Moreover, there are digital documents, reports, activity logs, images and biometrics information that are left as traces by criminals and there is also information archived from police entities. All of these data can be collected, represented and used as digital crime evidence in preventing and solving crimes. Crimes are not necessarily digital, but the traces left behind are or they can be digitized. There is a need for representing such digital information in a meaningful way and making sense of it in order to support the process of crime investigation and prevention. Ontologies and knowledge graphs, semantic similarity, text mining and other Artificial Intelligence approaches are useful for such purposes. It is possible to benefit from ontologies and knowledge graphs in different ways: intelligence gathering, reasoning over data, smarter searches and comparisons, open data publication purposes and the overall management of the crime solving and prevention process. In this Special Issue, we are looking for contributions that provide innovative methodologies, techniques, tools, approaches and insights into representing and reasoning with crime information. Keeping the chain of custody for all types of digital evidence and authenticating it in order to be admitted in court is also important to provide solutions. Biometrics, GDPR, data privacy issues, ethics and the legal aspects of crime prevention, detection and investigation are also of interest.

Dr. Sule Yildirim Yayilgan
Dr. Edlira Kalemi Vakaj
Guest Editors

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