1. Αποθετήριο Παραδοτέων Υποτρόφων Δράσεων ΕΣΠΑ Τριτοβάθμιας Εκπαίδευσης 2017-2023
2. Όλο το Αποθετήριο
3. Ερευνητικές ομάδες

Τύπος:	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	BioPrivacy: a behavioral biometrics continuous authentication system based on keystroke dynamics and touch gestures
Μέλος ερευνητικής ομάδας:	[EL] Στύλιος, Ιωάννης[EN] Stylios, Ioannis [EL] Σκάλκος, Ανδρέας[EN] Skalkos, Andreas
Επικεφαλής ερευνητικής ομάδας:	[EL] Κοκολάκης, Σπυρίδων[EN] Kokolakis, Spyros [EL] Καρύδα, Μαρία[EN] Karyda, Maria
Ημερομηνία:	26/05/2022
Περίληψη:	This paper is an extended version of SECPRE 2021 paper and presents a research on the development and validation of a BBCA system that is based on users keystroke dynamics and touch gestures on mobile devices. Session authentication schemes establish the identity of the user only at the beginning of the session, so they are vulnerable to attacks that tamper with communications after the establishment of the authenticated session. Moreover, smartphones themselves are used as authentication means, especially in two-factor authentication schemes, which are often required by several services. Whether the smartphone is in the hands of the legitimate user constitutes a great concern, and correspondingly whether the legitimate user is the one who uses the services. In response to these concerns, Behavioral Biometrics (BB) Continuous Authentication (CA) technologies have been proposed on a large corpus of literature. This paper presents a research on the development and validation of a BBCA system (named BioPrivacy), that is based on the user’s keystroke dynamics and touch gestures, using a Multi-Layer Perceptron (MLP). Also, we introduce a new behavioral biometrics collection tool, and we propose a methodology for the selection of an appropriate set of behavioral biometrics. Our system achieved the best results for keystroke dynamics which are 97.18% Accuracy, 0.02% Equal Error Rate (EER), 97.2% True Acceptance Rate (TAR), and 0.02% False Acceptance Rate (FAR).
Γλώσσα:	Αγγλικά
Σελίδες:	21
DOI:	10.1108/ICS-12-2021-0212
ISSN:	2056-4961
Θεματική κατηγορία:	[EL] Επιστήμη ηλεκτρονικών υπολογιστών και Πληροφορική, άλλοι τομείς[EN] Computer and Information sciences, miscellaneous
Λέξεις-κλειδιά:	Machine Learning; Behavioral Biometrics; Continuous Authentication; Mobile Devices; Multi-Layer Perceptron (MLP)
Κάτοχος πνευματικών δικαιωμάτων:	© 2020, Emerald Publishing Limited
Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη:	https://www.emerald.com/insight/content/doi/10.1108/ICS-12-2021-0212/full/html
Ηλεκτρονική διεύθυνση περιοδικού:	https://www.emerald.com/insight/publication/issn/2056-4961
Τίτλος πηγής δημοσίευσης:	Information and Computer Security
Τεύχος:	5
Τόμος:	30
Σελίδες τεκμηρίου (στην πηγή):	687-704
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 “BioPrivacy: Development and validation of a Behavioral Biometrics Continuous Authenti-cation System” (MIS 5052062).
Εμφανίζεται στις συλλογές:	Ερευνητικές ομάδες