Cryptographic technologies and encrypted channel communications have become a standard security pre-requisite among government and industry protocols, schemes and infrastructure. Practical quantum computing, when available to cyber adversaries, will break the security of nearly all modern public-key cryptographic systems. Practical quantum computing, when available to cyber adversaries, will break the security of nearly all modern public-key cryptographic systems. Consequently, all secret symmetric keys and private asymmetric keys that are now protected using current public-key algorithms, as well as the information protected under those keys, will be subject to exposure. This includes all recorded communications and other stored information protected by those public-key algorithms, the so-called Harvest Now Decrypt Later (HNDL) paradigm. Any information still considered to be private or otherwise sensitive will be vulnerable to exposure and undetected modification. Once exploitation of Shor’s algorithm becomes practical, protecting stored keys and data will require re-encrypting them with a quantum-resistant algorithm and deleting or physically securing “old” copies (e.g., backups). Integrity and sources of information will become unreliable unless they are processed or encapsulated (e.g., re-signed or timestamped) using a mechanism that is not vulnerable to quantum computing-based attacks. PQ-NEXT will focus on developing a comprehensive framework to facilitate the seamless transition to post-quantum cryptographic standards. This includes creating a catalog of PQC algorithms, maintenance tools, and a quantum programming language with advanced features like high-performance simulation and hybrid quantum-classical optimization, ensuring crypto-agility and security against quantum threats for large-scale pilots, targeting the financial, critical infrastructure, digital identities and telco industries.

Current evidence suggests that the global fight against corruption faces serious challenges: policy decisions are not well informed, the corruption landscape is complex and enormous, while measuring corruption is so far mostly based on subjective approaches, and there is lack of appropriate technological tools to support anti-corruption. To address these challenges, FALCON is designed and dedicated to support the composition, update and management of comprehensive corruption intelligence pictures, within domains and jurisdictions of interest. This will be accomplished following a multi-actor, evidence-based, data-driven approach, building upon existing assets and prior work of consortium partners. FALCON will, first, develop and validate objective and actionable indicators (individual and composite) of corruption that can be used to inform policy decisions. Second, it will design, implement and integrate powerful data analytics tools, data pipelines and applications that support the management of the entire lifecycle of corruption intelligence pictures. This will enable comprehensive corruption risk assessment, informed policy making, and improved anticorruption law enforcement. FALCON will be piloted in four corruption domains – corruption schemes at border crossings, sanction circumvention by kleptocrats/oligarchs, public procurement fraud, conflicts of interest of politically exposed persons (PEPs) – involving law enforcement experts (police authorities and border guards) from six (6) European countries and other key actors (i.e., GovTech providers, academia, financial intermediaries, policy makers, NGOs, and civil society). FALCON’s implementation will be incremental and iterative, forming synergies between SSH and technological expertise, and will adhere to the principles of Trustworthy AI and responsible research and innovation. Lastly, FALCON has defined specific key exploitable results and performance indicators for measuring its progress and success.