The aim of this research is to explore whether learning from investigating crime in geographic locations can be applied to online crime.
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Data from the Crime Survey of England and Wales clearly show that cyber crime is a substantial problem for the public, accounting for about 50% of all crime. Offences range in size, from everyday incidents to the spectacular, and in nature, from malicious attacks to those motivated by financial gain.
As more and more services go online, the problem is likely to grow in volume, as is the range of crimes committed.
Cyber crime differs from traditional urban crime in a number of important ways: for example, it is asymmetric, in the sense that a single offender can commit many offences, often with relative ease.
Nevertheless, there are several aspects of criminal behaviour which are common to both, particularly in relation to the awareness and evaluation of targets. The aim of the proposed project is to examine whether lessons learned in relation to urban crime can be applied or adapted in online environments.
The primary aim of the proposed work is to develop a general framework for the analysis of crime occurring in non-geographic spaces. The range of such crimes (and indeed spaces) is very broad, with each likely to pose particular challenges and require bespoke treatment.
Since it would be infeasible to consider all of these, the aim of this research is to identify general principles and demonstrate how they can be applied in several illustrative cases identified in discussion with law enforcement and industry. These would act as proofs-of-concept for the overall approach and motivate its application to a more extensive range of issues.
- Data comes from cybercrime security companies.
- Main methods are based on machine learning.