Artificial intelligence and UMF standard for interoperability of facial recognistion and person-centric OSINT
| dc.contributor.author | Ahmed el Rahwan, Amr | en |
| dc.date.accessioned | 2023-06-14T09:18:29Z | |
| dc.date.issued | 2023-06-14 | |
| dc.identifier.uri | https://repository.ihu.edu.gr//xmlui/handle/11544/30298 | |
| dc.rights | Default License | |
| dc.subject | Multiple-Identity | en |
| dc.subject | OSINT | el |
| dc.subject | Universal Message Format | el |
| dc.subject | UMF | el |
| dc.subject | Open Source Intelligence | el |
| dc.subject | Interoperability | el |
| dc.subject | Cross-Border | el |
| dc.subject | Artificial Intelligence | el |
| dc.title | Artificial intelligence and UMF standard for interoperability of facial recognistion and person-centric OSINT | en |
| heal.abstract | During daily operations, law enforcement and border security officials face challenges such as multiple identity, fraud, lack of cross-border interoperability, and complexity of OSINT “Open Source Intelligence” investigations. These challenges occur because the information systems for law enforcement and border security were implemented in silos, the data is stored in data sources on the national, regional, and international levels, and open data sources and the stored identityrelated data vary between biographics, biometrics, and metadata. Moreover, the mentioned challenges have a negative impact on the time consumed in investigations, accurate identification of wanted suspects, and protection of innocent people. Finally, the Open Source Intelligence (OSINT) investigation process is not automated, consumes a lot of time, and is overwhelming. When border security and law enforcement officers use methods of OSINT to investigate terrorism and serious crime, it is very difficult to match and link the identity-related data and facial images of the suspects stored in the EU systems, Cross-Border systems, and open sources. | el |
| heal.academicPublisher | IHU | el |
| heal.academicPublisherID | ihu | en_US |
| heal.access | embargo | |
| heal.advisorName | Baltatzis, Dimitrios | el |
| heal.committeeMemberName | Serketzis, Nikolaos | en |
| heal.dateAvailable | 2024-06-13T21:00:00Z | |
| heal.language | en | en_US |
| heal.license | http://creativecommons.org/licenses/by-nc/4.0 | en_US |
| heal.publicationDate | 2024-12-31 | |
| heal.recordProvider | School of Science and Technology, MSc in Cybersecurity | en_US |
| heal.type | masterThesis | en_US |
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