Advanced Modelling of Cybercriminal Careers (AMOC):New Tech and Intelligence from Online Evidence Bases

Dates: January 2018 – March 2021
Lead researchers: Professor Awais Rashid, Dr Emma Williams, Dr Claudia Peersman, Dr Matthew Edwards, University of Bristol

Overview

Recent research in debriefing arrested criminals has identified that cybercrime is not a solitary and anti-social activity, but one wherein online social interactions play a critical role – namely, in the recruitment, training and professional advancement of criminals. For this reason, investigating these social interactions is important to understanding the dynamics leading to initial engagement in cybercrime, continued careers and potential retirement. This project aimed to understand the social and economic development of cybercriminal careers.

To do this, the work focuses on the potential for combining advanced data mining of these social interactions, with qualitative methods drawn from psychology, criminology and (socio)linguistics to form a detailed understanding of the characteristics of cyber offenders, their behavioural patterns and their career progression in cybercrime. The project resulted in the production of new techniques and software tools to support law enforcement agencies to detect and investigate cyber offenders, cyber threats and online networks.

It’s hoped these tools will allow cybercrime investigators to detect cyber offenders, analyse their criminal activities and behaviour; assign degrees of importance and urgency to items of evidence in order to assess the potential danger to society, and find useful evidence in a timely manner.

Policy implications

The project findings will have relevance for law enforcement and policy stakeholders. The findings are intended to inform evidence-based approaches to disrupting cybercriminal activities on dark-net markets.

Methods

A web-based survey; qualitative analyses for building an assessment framework; quantitative analyses using text mining, natural language processing and machine learning techniques.

Funders: Home Office
External collaborators: The National Crime Agency, the Dutch National High Tech Crime Unit, the Shadowserver Foundation and the UN Office on Drugs and Crime.

Skills

Posted on

December 9, 2021