Technology, training and knowledge for Early-Warning / Early-Action led policing in fighting Organised Crime and Terrorism

Informations projet

COPKIT

N° de convention de subvention: 786687

DOI

10.3030/786687

Projet clôturé

Date de signature de la CE 29 Mai 2018

Date de début 1 Juin 2018

Date de fin 30 Septembre 2021

Financé au titre de

• Secure societies - Protecting freedom and security of Europe and its citizens

Coût total

€ 4 986 973,75

Contribution de l’UE

€ 4 986 973,75

Coordonné par

INGENIERIA DE SISTEMAS PARA LA DEFENSA DE ESPANA SA-SME MP
Spain

Periodic Reporting for period 2 - COPKIT (Technology, training and knowledge for Early-Warning / Early-Action led policing in fighting Organised Crime and Terrorism)

Période du rapport: 2019-12-01 au 2021-09-30

Résumé du contexte et des objectifs généraux du projet

The COPKIT project addresses the problem of analysing, preventing, investigating and mitigating the use of new information and communication technologies by organised crime and terrorist groups. This question is a key challenge for policy-makers and LEAs due to the complexity of the phenomenon, the quantity of factors and actors involved, and the great set of criminal and terrorist technological activities in support of OC and terrorist actions. It is a clear VUCA world effect (volatility, uncertainty, complexity and ambiguity).
EUROPOL who is involved in COPKIT as head of its Advisory Board, in its SOCTA 2017 report "Crime in the Age of Technology" states that "This is now, perhaps, the greatest challenge facing LEAs around the world". In VUCA environment, anticipation is the way forward for LEA to change the situation from “lagging behind” innovation in criminal behaviour to “being ahead of the curve”. COPKIT proposes an intelligence-led Early Warning (EW) / Early Action (EA) system, directly related to the methodological approach used by EUROPOL in SOCTA. “Intelligence-led policing” offers a framework to guide operations, prioritizing needs and optimizing resources. EW explain how crimes are evolving, identifying "weak signals", warnings, new trends, and being a basis for assisting decision makers, both strategic and operational levels, in order to develop EA (preparedness, mitigation, prevention and other security policies). COPKIT aims to create such a technological intelligence and knowledge ecosystem for LEAs, to fight OCT.
Organized crime and terrorism are evolving phenomena with high societal impacts so the more we act upon the warnings on the longest timescales, the more effectively our societies will be tackling the risks generated by the use of new technologies by criminal groups.
The overall COPKIT objectives are:
- Apply new EW/EA-led policing technologies for improved situational awareness by analysing and combining data from relevant and reliable sources to identify, understand and counteract new threats and trends in crime.
- Develop a toolkit for knowledge production and exploitation in investigative and strategic analysis work to support the EW-EA paradigm by leveraging cross-level knowledge and support the analysts in his tasks, from knowledge discovery via situation assessment to forecasting.
- Ensure that the new tools, detection capabilities and knowledge-sharing respect EU data protection regulation and ethical principles.
- Develop innovative curricula for educating and training LEAs for the methodological and workflows aspects of EW/EA-led policing based on comparative analysis of our iconic use-case and the necessary training for use of the corresponding new tools.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

Based on the specification of the technical requirements, steered by LEAs, the end-users needs, expectations and constraints, collected with the support of developed appropriate scenarios, use cases and an operational and needs/gaps analysis, and taking into account the identified legal, societal and ethical constraints, acting as a framework for the project, COPKIT defined, designed and implemented the COPKIT Early Warning (EW) / Early Action (EA) ecosystem. COPKIT produced a toolkit with 19 components encompassing the various capability of the analysis circle (data acquisition, Information Extraction, knowledge storage and management. intelligence discovery, decision support and forecasting). These technical components composing this toolkit support the transverse requirements necessary to the operationalization of the EW/EA concepts: security management, adaptive privacy and uncertainty management as well the HMI supporting the innovative workflows for analysts. The transverse activities included the elaboration of a methodology for the integrated privacy, ethical and social impact assessment of COPKIT ecosystem and its application to these components. The technical components were tested by the LEA’s partners and demonstrated and evaluated during the three main demonstration exercises with a broader audience with LEAs.
Following the designed dissemination and exploitation strategy, and the communication plans, defined at the first stages of the project, COPKIT had a strong dissemination, with a very active on-line presence. Partners presented the project at numerous workshops and other events, collaborated with other linked projects and issued several scientific publications.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

COPKIT proposes a new approach to policing, an intelligence-led Early Warning (EW) / Early Action (EA). The investigations based on user stories provided by LEAs have shown that the EW/EA approach could help LEAs in improving the efficiency of the investigation of crimes involving criminal use of new technologies. Further, capability in the strategic analysis could also be improved, enabling LEA to stay ahead of the curves of new development in the way OCGs make use of new technologies. This was studied in the criminal use of the dark net for firearm trafficking and Crime as a Service but is likely to be generalizable to other types of crimes. Innovative workflows and HMI for analysts have been developed enabling the efficient use of multi-level intelligence
Knowledge is central to the EW/EA paradigm. Therefore the COPKIT project has investigated innovative technical approaches in which knowledge of analysts can be combined with automated processes in several ways:
• by allowing the LEA operator to intervene efficiently (human in the loop) or,
• by making use of Artificial Intelligence and Machine Learning techniques that allow incorporation of expert knowledge (Knowledge constraint Machine Learning).
The evaluation of the developed tools showed the relevance of the techniques and their potential for improvement in LEA strategic and operational work, particularly in low volume crimes or when data are expensive to obtain and label. The tools developed encompass diverse analysis activities (data acquisition, information extraction, assessment and fusion and forecasting) showing that the approach is relevant throughout the entire analysis cycle. Many of the techniques used are characterized by strong explainability properties, desirable for responsible usage of AI techniques. To further facilitate the uptakes of AI techniques and the procurement process for LEAs, COPKIT developed a software infrastructure enabling secure testing of new AI component at LEA premises.
The EW/EA paradigm relies on the ability to share data and knowledge. The COPKIT project realized and evaluated innovative solutions to secure sharing, adaptive privacy and awareness of the issue of uncertainty and encompassing both the technical infrastructure and the human / operator aspects. These innovations facilitate a more efficient and proportional use of data in the domain of fighting against crime and terrorism responding to the increasing request by the society for responsible use of private data in the domain and increased trust in the policing organization.

COPKIT Consortium

COPKIT website