Examples of relevant techniques include: examination of digitally captured signatures, identification of voice cloning and of deepfakes; detection and recognition of persons/objects/logos; speaker diarisation and identification; speech recognition and transcription into text; automatic classification of text based on risk factors; optical character recognition; named entity recognition; concept extraction, extraction of entities and relations between them in unstructured text; multimodal analytics, in order to discover insights and patterns in large volumes of data through clustering, as well as the identification of user communities and key actors in the social networks being formed online; automatic correlations among all available sources, as well as cross-checking, cross-matching and mapping information between different cases, i.e. cross-reference with existing records in databases of Police Authorities.

Identification of perpetrators can also be enhanced by detecting their online behaviour and habits, e.g. which days/hours they are used to login/logout.

Taking advantage of these modern technologies will require Police Authorities to move away from business models based on data input to data evaluation. It will require robust and reliable information management structures that encompass all aspects from data collection to handling, evaluation, exploitation and data security. In particular, key principles such as lawfulness of processing and data minimisation should apply to ensure that Police Authorities conduct data analysis in full compliance with fundamental rights and EU privacy and personal data protection legal framework. For example, it may be necessary to filter and reduce large datasets to what is relevant for operational support activities and in investigations, and/or apply methods such as differential privacy. Hence, all these efforts should also reconcile big data analysis and data protection, i.e.: explore challenges to conduct big data analysis in accordance with data minimisation principles and data protection by default standards, propose possible models and scientific options to tackle the challenge, and develop solutions (digital tools) that meet the challenge, focusing on triage and clustering functions. Possibilities of assessing and preventing bias and discrimination as a result of big data analysis should be analysed too. The successful proposal should thus help framing the issue of big data analysis for Police Authorities, providing guidelines as well as operational tools to comply with EU data protection law.

The successful proposal should build on the publicly available achievements and findings of related previous national or EU-funded projects as well as create synergies with similar on-going security research projects from the Calls 2021-2022 on Fighting Crime and Terrorism in the area of modern information analysis, in order to avoid duplication and to exploit complementarities as well as opportunities for increased impact.