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Travelling Intelligence Against Crime and Terrorism

Periodic Reporting for period 1 - TENACITy (Travelling Intelligence Against Crime and Terrorism)

Période du rapport: 2022-09-01 au 2024-02-29

LEAs use the data in their information systems as their basis for making decisions that affect the safety of European citizens. According to a recent report of the European Court of Auditors on the EU Information Systems use, it has been found out that individual countries have different perception and methodologies on how data management should be addressed; officers from LEAs have stated that not all datasets are included in their systems, while other data is either not complete and accurate or not entered in a timely manner. The same report states that there are regulatory and “cultural” issues, according to which some countries do not make all the functions offered in the central EU systems available through their national systems. TENACITy envisions to address these challenges by proposing a 3-pillar approach: (a) Modern and effective tools for exploitation of travel intelligence data by security authorities: TENACITy proposes an interoperable open architecture for the integration and analysis of multiple transactional, historical and behavioural data from a variety of sources, by exploiting game changing digital technologies; (b) Training and sensitisation of LEAs’ personnel: TENACITy envisions the design of a “living lab” to be established to organise hackathons, workshops for all relevant stakeholders who would benefit from the use of passenger data and digital technologies proposed; (c) Holistic approach to crime prevention: TENACITy vision is to implement and demonstrate a Travel Intelligence Governance Framework that will incorporate a holistic approach to crime prevention, will ensure that the proposed digital technologies will support the identification of the modus operandi of criminal and terrorism organizations and will include policy makers in the governance process, examining how the new tools will provide new capabilities to shape the regulations.
The project began with creating and distributing a detailed survey to assess EU member states' capabilities in handling API/PNR data, alongside a review of the state-of-the-art in travel intelligence data sources and handling methods. This foundational work was crucial for identifying improvement areas and benchmarking against current practices.

Stakeholder engagement was a significant focus, with workshops and surveys conducted to gather insights on border security and trust-building measures. The feedback shaped the user needs and test scenarios, enhancing the project's strategic focus. To address the identified challenges, criminal patterns and risk factors linked to serious crimes were analyzed, and synthetic PNR datasets were developed to simulate real-world data scenarios securely.

The launch of the first version of the TENACITy Tools and the TIGF marked a milestone, supported by an online workshop to discuss technology needs with end-users. Training methodologies were tailored to various trainee profiles, employing experiential learning principles, resulting in three training curricula and an interactive platform. A Physical Living Lab was also established to foster real-time experimentation and feedback. The Living Lab introduced the TENACITy tools to end-users, garnering interest from several Passenger Information Units (PIUs) and setting up an infrastructure for continuous tool integration and validation. Stakeholder consultations addressed data quality assessment and pseudonymization techniques.

Additionally, a comprehensive Dissemination and Communication Plan and Exploitation strategy were established, enhancing project branding and facilitating synergies with key related projects. The project's strategic focus was continuously refined through feedback from a diverse group of stakeholders, including law enforcement, customs officials, and citizens, ensuring that it met evolving needs and expectations.
TENACITy will advance beyond the state of the art in several fronts:

Travel Intelligence Governance Framework: TENACITy’s ambition is to offer a response to the incompatibility of intelligence and respect for human rights, by blending together the different dimensions and perspectives (i.e. technological advances, legal and ethics constraints, societal concerns) into a reinvigorated oversight that will safeguard and protect human rights without hindering agencies' ability to maintain public safety. This will be achieved with the development of a mechanism for improved prevention, investigation, and mitigation of impacts of crime, including of new/emerging criminal modi-operandi. This mechanism will invite decision-makers and stakeholders to become -in a systematic and comprehensive way- integral part of the governance process aimed at understanding the interplay of expectations and requirements of policy-makers, LEAs and passengers.

Development of an Interoperable open Architecture and Digital Tools on the use of Travel Intelligence: TENACITy will go beyond the state of the art by applying web intelligence to determine relevant behavioural indicators. Doing so will help to detect outliers or anomalies, discover previously unknown trends, associations and rules, and continually monitor data streams as a preventive measure. TENACITy will enable LEAs to search, acquire and structure online data related to the subject under investigation. In light of this, investigators will be able to retrieve not only the requested PNR data, but also to perform background checks of this individual, the results of which can be validated versus their PNR, with respect to the current legal framework (DIRECTIVE 2016/681) as well as the privacy and ethics restrictions (e.g. GDPR). This will be achieved by having always a human-in-the-loop in the OSINT process, applying pseudonymisation techniques for private/sensitive information and using transient data whenever applicable. TENACITy will also build models able to accurately predict dynamic, individual behavior something that machine learning methods due to their statistical nature fail to do. Moreover, this combination will render the proposed approach robust to adversarial environments, another weakness for most AI approaches that the combined approach of TENACITy aspires to eradicate.