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Mobile phone user authentication with grip gestures using pressure sensors
- Source :
- MoMM
- Publication Year :
- 2015
- Publisher :
- Emerald, 2015.
-
Abstract
- Purpose – User authentication is generally used to protect personal information such as phone numbers, photos and account information stored in a mobile device by limiting the user to a specific person, e.g. the owner of the device. Authentication methods with password, PIN, face recognition and fingerprint identification have been widely used; however, these methods have problems of difficulty in one-handed operation, vulnerability to shoulder hacking and illegal access using fingerprint with either super glue or facial portrait. From viewpoints of usability and safety, strong and uncomplicated method is required. Design/methodology/approach – In this paper, a user authentication method is proposed based on grip gestures using pressure sensors mounted on the lateral and back sides of a mobile phone. Grip gesture is an operation of grasping a mobile phone, which is assumed to be done instead of conventional unlock procedure. Grip gesture can be performed with one hand. Moreover, it is hard to imitate grip gestures, as finger movements and grip force during a grip gesture are hardly seen by the others. Findings – The feature values of grip force are experimentally investigated and the proposed method from viewpoint of error rate is evaluated. From the result, this method achieved 0.02 of equal error rate, which is equivalent to face recognition. Originality/value – Many researches using pressure sensors to recognize grip pattern have been proposed thus far; however, the conventional works just recognize grip patterns and do not identify users, or need long pressure data to finish confident authentication. This proposed method authenticates users with a short grip gesture.
- Subjects :
- Password
Authentication
General Computer Science
Pressure sensor
Computer science
business.industry
Usability
Computer security
computer.software_genre
User authentication
Facial recognition system
Grip gesture
Theoretical Computer Science
Fingerprint
Feature (computer vision)
Human–computer interaction
Phone
Mobile phone
Computer vision
Artificial intelligence
business
Mobile device
computer
Simulation
Gesture
Subjects
Details
- ISSN :
- 17427371
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- International Journal of Pervasive Computing and Communications
- Accession number :
- edsair.doi.dedup.....a9ea29b0fb29d490526abdd763433bde
- Full Text :
- https://doi.org/10.1108/ijpcc-03-2015-0017