Konferenzbeitrag
Diversity and Novelty MasterPrints: Generating Multiple DeepMasterPrints for Increased User Coverage
Vorschaubild nicht verfügbar
Volltext URI
Dokumententyp
Text/Conference Paper
Zusatzinformation
Datum
2022
Autor:innen
Zeitschriftentitel
ISSN der Zeitschrift
Bandtitel
Quelle
Verlag
Gesellschaft für Informatik e.V.
Zusammenfassung
This work expands on previous advancements in genetic fingerprint spoofing via the
DeepMasterPrints and introduces Diversity and Novelty MasterPrints. This system uses quality diversity
evolutionary algorithms to generate dictionaries of artificial prints with a focus on increasing
coverage of users from the dataset. The Diversity MasterPrints focus on generating solution prints
that match with users not covered by previously found prints, and the Novelty MasterPrints explicitly
search for prints with more that are farther in user space than previous prints. Our multi-print search
methodologies outperform the singular DeepMasterPrints in both coverage and generalization while
maintaining quality of the fingerprint image output.