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https://hdl.handle.net/123456789/1363| Τύπος: | Ανακοίνωση σε συνέδριο; Πρακτικά συνεδρίου; Κεφάλαιο σε πρακτικά συνεδρίου |
| Τίτλος: | StegoPass – Utilization of steganography to produce a novel unbreakable biometric based password authentication scheme |
| Συγγραφέας: | [EL] Καραμπίδης, Κωνσταντίνος[EN] Karampidis, Konstantinos [EL] Λινάρδος Ευάγγελος[EN] Linardos, Euangelos [EL] Καβαλλιεράτου, Εργίνα[EN] Kavallieratou, Ergina |
| Ημερομηνία: | 22/09/2021 |
| Περίληψη: | In the digital era we live, trustworthy verification schemes are required to ensure security and to authenticate the identity of an individual. Traditional passwords were proved to be highly vulnerable to attacks and the need of adopting new verification schemes is compulsory. Biometric factors have gained a lot of interest during the last years due to their uniqueness, ease of use, user convenience, and ease of deployment. However, recent research showed that even this unique authentication factors are not inviolable techniques. Thus, it is necessary to employ new verification schemes that cannot be replicated or stolen. In this paper we propose the utilization of steganography as a tool to provide unbreakable passwords. More specifically, we obtain a biometric feature of a user and embed it as a hidden message in an image. This image is then utilized as a password, the so-called StegoPass. Reversely, when a legit user or an attacker tries to unlock a device or an application, the same biometric feature is captured and embedded with the same steganography algorithm into the picture. The hash key of the resulted stego image in both cases is produced and if there is a complete match, user is considered as authenticated. To ensure that the proposed StegoPass cannot be replicated, we have conducted experiments with state-of-the-art deep learning algorithms. Moreover, it was examined whether Generative Adversarial Networks could produce exact copies of the StegoPass to fool the suggested method and the results showed that the proposed verification scheme is extremely secure. |
| Γλώσσα: | Αγγλικά |
| Σελίδες: | 10 |
| DOI: | 10.1007/978-3-030-87872-6_15 |
| ISBN: | 978-3-030-87871-9 |
| Θεματική κατηγορία: | [EL] Επιστήμη ηλεκτρονικών υπολογιστών[EN] Computer Science |
| Λέξεις-κλειδιά: | Steganography; Biometrics; Neural Networks; Generative adversarial networks |
| Κάτοχος πνευματικών δικαιωμάτων: | © 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG |
| Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη: | https://link.springer.com/chapter/10.1007/978-3-030-87872-6_15 |
| Ηλεκτρονική διεύθυνση περιοδικού: | https://link.springer.com/book/10.1007/978-3-030-87872-6 |
| Τίτλος πηγής δημοσίευσης: | Proceedings of the 14th International Conference CISIS2021 and 12th International Conference ICEUTE2021 |
| Τόμος: | AISC, volume 1400 |
| Σελίδες τεκμηρίου (στην πηγή): | 146-155 |
| Σειρά δημοσίευσης: | Advances in Intelligent Systems and Computing |
| Όνομα εκδήλωσης: | 14th International Conference on Computational Intelligence in Security for Information Systems |
| Τοποθεσία εκδήλωσης: | Bilbao, Spain |
| Ημ/νία έναρξης εκδήλωσης: | 22/09/2021 |
| Ημ/νία λήξης εκδήλωσης: | 24/09/2021 |
| Σημειώσεις: | This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014–2020» in the context of the project “Creation of a Multimodal Biometric Password by using Steganography” (MIS 5050338).” |
| Εμφανίζεται στις συλλογές: | Ερευνητικές ομάδες |
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