Horizon Europe · Global Challenges and European Industrial Competitiveness
Trusted, secure, quality future digital travel credentials
Call summary
From the official text, opening part
Expected Outcome: Project results are expected to contribute to some or all of the following expected outcomes: Development, testing and integration of issuance, validation and sharing capabilities for possible future types (beyond Type 1) of Digital Travel Credentials (DTC); Integration of innovative, on-the-move, biometrics and remote biometric acquisition modalities to support the use of DTCs; Improved secure connectivity and interoperability for future DTCs; Improved capability of issuance of emergency travel documents and/or emergency DTCs. Scope: Issuance, verification and management of digital travel credentials (DTCs) is relevant for border management, immigration and visa management. Furthermore, it could also be relevant to combat illicit activities such as terrorism, crime or frauds. This topic aims at supporting research and innovation that explore, develop and test enhanced … more
Border and coastguardsBorder and external securityEnsure Identification and control of goods and peopleSecurityBordersbiometricscapabilitiesdigital travel credentialsemergency DTCs
Academics who may be relevant
By subject fit
4-
%67ZEYNEP İNEL ÖZKİPER
Shared topics: Biometric Identification and Security
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%54MOHAMMED MOHAMMED SAYIM KHALIL
Shared topics: Biometric Identification and Security
Overlapping papers: Fingerprint-Based Cryptographic Identity: A Custom Recognition Pipeline with Key Pair Generation (2025) · AUTHENTICATION OF FINGERPRINT BIOMETRICS ACQUIRED USING A CELLPHONE CAMERA: A REVIEW (2013)
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%46ATİLA BOSTAN
Shared topics: Biometric Identification and Security
Overlapping papers: Biometric Verification on e-ID-Card Secure Access Devices: A Case Study on Turkish National e-ID Card Secure Access Device Specifications (2017)
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%40MONIREH NOROUZI SOUFIANI
Research topics: Network Security and Intrusion Detection · Advanced Malware Detection Techniques · IoT and Edge/Fog Computing
The fit is computed by code on every request. The call text (title, keywords, start of the official description) is compared with three sources: semantic similarity to the academic profile (50%), shared distinctive terms in YÖKSİS keywords and OpenAlex topics (25%) and publication content — titles, English abstracts and their Turkish translations (25%). Thanks to the translations, Turkish calls also meet papers written in English. Common words weigh little; below 40% is not shown. A subject hint only — not an eligibility, capacity or merit assessment. Hidden profiles are never listed.