Fighting crime through technology and collaboration
Today, it seems like everything is going digital – and the world’s criminal underbelly is no exception. In fact, organised crime and terrorist organisations are adopting new information and communication technologies at an alarming rate. As law enforcement agencies (LEAs) struggle to keep up, it becomes increasingly difficult for them to do their jobs. According to Europol, the technology gap between criminal organisations and police is “perhaps the greatest challenge facing LEAs around the world.” For the EU-funded COPKIT project, the answer to closing this gap is intelligence-led policing. “Intelligence-led policing offers a frame to guide law enforcement operations, prioritise needs and optimise resources,” says Raquel Pastor, a researcher at Engineering Systems for the Defence of Spain (Isdefe) and COPKIT coordinator. “By taking a data-driven approach to policing, LEAs will be better able to analyse, investigate, mitigate and prevent organised crime’s use of new technologies.”
An early warning/early action system
At the heart of the project is an innovative early warning (EW)/early action (EA) system, which Pastor says can be used to improve an LEA’s situational awareness. “The EW/EA approach helps LEAs improve the efficiency of how they investigate crimes involving the criminal use of new technologies,” she remarks. “This system can also improve their strategic analysis capabilities, allowing LEAs to stay one step ahead of how criminal organisations use technology to commit crimes.” The EW/EA system uses a range of artificial intelligence and machine learning techniques to gather and analyse data in both large and small volumes. The system then uses this data to help the analyst discover how crimes are evolving and identify weak signals, warnings and new trends. By flagging potential and emerging threats, decision makers can then develop EA plans to address the threat.
A more powerful response to criminal activity
The EW/EA system addresses one of policing’s biggest shortcomings: the siloing of information. For example, current methods do not take advantage of the fact that local policing organisations can continuously feed locally analysed crime data into models and share this information between specialists, departments and, possibly, with other agencies. “The reality is that no single team has the knowledge, resources, data or time to feed such a system,” explains Pastor. “That’s the beauty of COPKIT, it provides an approach and the tools, including a knowledge base, for LEAs from across Europe to generate, share and use knowledge and collaborate to better fight crime.” According to Pastor, the COPKIT approach will increase and leverage the understanding of how criminal activities evolve. It also allows such information to be continuously updated and, because one can extract non-sensitive patterns and knowledge, avoids the pitfalls of sharing sensitive information. “Sharing and continuously updating the models and patterns about crime across the many LEAs operating in different Member States ensures a more rapid dissemination of new intelligence – and a more powerful response to criminal activity,” says Pastor. But perhaps more importantly, COPKIT is a tool that LEAs will actually use. “This isn’t only a theory, it’s about operational tools that police are excited about incorporating into their regular workflows,” adds Pastor. COPKIT partners are actively working to make its solutions available to LEAs across Europe, increasing their capability to fight current and future criminal activities and supporting a more secure Europe.
Keywords
COPKIT, crime, technology, data, law enforcement agencies, criminal activity, organised crime, terrorist organisations, Europol, intelligence-led policing, police, artificial intelligence, machine learning
