Distributed Ledger Technologies Implementation in Internal Organizational Workflows and Support Applications for Cooperation among National Security Institutions
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Distributed Ledger Technologies Implementation in Internal Organizational Workflows and Support Applications for Cooperation among National Security Institutions

DefenceDigital government

Region

national

Partners

2 partners

Phase

Ongoing

Start

Sep 16, 2024

End

Sep 15, 2026

Timeline

No timeline events available yet.

Abstract

The project aims to develop, test, and operationalize a multimedia data manipulation platform, encompassing data collection, preprocessing, storage, segregated user access, and their secure transformation based on cryptographic keys and signatures within a platform that integrates DLT-specific infrastructure and protocols. (Distributed Ledger Technology). Using techniques for federating artificial intelligence tools, the project aims to develop a modern solution for extracting useful information from multiple sources centered on textual data.

Objectives

  1. The development of technological concepts, methods, and algorithms based on distributed ledgers (TRL 3).
  2. Research, design, experimentation, and laboratory validation of a technological solution for the digital recording of transactions and their details in multiple locations simultaneously (TRL 4).
  3. Creating a platform that allows the sharing of information and know-how between institutions that implement/wish to implement blockchain-based solutions, as well as creating complementarity between the actions and instances of use of these solutions, validating the results through testing and evaluation of demonstrators/functional models in the operational environment. (TRL 8)
  4. Operationalizing the platform and demonstrating the characteristics regarding availability, confidentiality, efficiency, security, traceability, and scalability (TRL 8).

Modules:

  1. User Interface Design: Providing an intuitive and easy-to-use interface with basic functionalities.
  2. Data Collection: Collecting and ingesting data from multiple sources.
  3. Preprocessing and Storage: Preparing the collected data for storage and analysis.
  4. Blockchain/DLT: Implementing secure storage and transaction management using DLT.
  5. Analysis: Using AI for data analysis, entity recognition, and language translation.
  6. Risk Assessment and Predictive Analysis: Development of AI models for risk assessment based on analyzed data.
  7. Frontend Implementation: Building and implementing the frontend components of the platform.
  8. Compliance and Security: Ensuring the platform's compliance with GDPR and other security regulations.
  9. Testing and QA: Conducting initial testing to validate the main functions and identify possible improvements.
  10. Hardware Infrastructure: Configuring the hardware for the DLT platform and AI processing.
  11. Reporting and Documentation: Documenting results and generating reports, ensuring knowledge distribution.

Research Domains

Software and Hardware for AI