Title :

Virtual Keyboard Logging Counter-Measures Using Human Vision Properties

Author(s) :

Bacara, Christophe [Auteur correspondant]
Université de Lille, Sciences et Technologies
Lefils, Valentin [Auteur]
Université de Lille, Sciences et Technologies
Cartigny, Julien [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Extra Small Extra Safe [2XS]
Grimaud, Gilles [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Extra Small Extra Safe [2XS]
Wary, Jean-Philippe [Auteur]
Orange Labs [Issy les Moulineaux]

Conference title :

Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on

City :

New York, NY

Country :

Etats-Unis d'Amérique

Start date of the conference :

2015-08-24

English keyword(s) :

authentication
keyboards
malware
visualization
human vision properties
human-readable virtual keyboard
malware landscape
motion perception
screenshot-based keylogging method
simulation
virtual keyboard logging counter-measures
visual interpolation

HAL domain(s) :

Informatique [cs]/Cryptographie et sécurité [cs.CR]
Informatique [cs]/Interface homme-machine [cs.HC]

English abstract : [en]

This paper describes keylogging counter-measures for virtual keyboards, widely used to authenticate in various applications and contexts, such as online banking services or touch screen mobile devices. Due to this massive ...
Show more >This paper describes keylogging counter-measures for virtual keyboards, widely used to authenticate in various applications and contexts, such as online banking services or touch screen mobile devices. Due to this massive use and to the malware landscape, the security of a virtual keyboard at authentication time is fundamental. Our work is based upon several human vision properties like motion perception, visual as simulation and visual interpolation. We, first, generate a frame filled with noise and then we manipulate this noise in order to make a user see shapes, e.g. letters or digits. The recognition of these shapes by a malware would require high analysis capabilities to automatize. This way, we achieved to make a human-readable virtual keyboard resilient to a large scope of screenshot-based keylogging methods.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL