Journal article
Multi-modal decision fusion for continuous authentication
Computers & electrical engineering, v 41(C)
Jan 2015
Abstract
[Display omitted]
•Behavioral biometrics: keystroke dynamics, mouse movement, stylometry.•A parallel binary decision fusion architecture with 11 sensors.•A dataset collected from 67 users each working in an office environment for a week.•Achieve below 1% error rates (FAR, FRR) after only 30s of activity.•Characterize robustness of system to adversarial attacks.
Active authentication is the process of continuously verifying a user based on their on-going interaction with a computer. In this study, we consider a representative collection of behavioral biometrics: two low-level modalities of keystroke dynamics and mouse movement, and a high-level modality of stylometry. We develop a sensor for each modality and organize the sensors as a parallel binary decision fusion architecture. We consider several applications for this authentication system, with a particular focus on secure distributed communication. We test our approach on a dataset collected from 67 users, each working individually in an office environment for a period of approximately one week. We are able to characterize the performance of the system with respect to intruder detection time and robustness to adversarial attacks, and to quantify the contribution of each modality to the overall performance.
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Details
- Title
- Multi-modal decision fusion for continuous authentication
- Creators
- Lex Fridman - Drexel UniversityAriel Stolerman - Drexel UniversitySayandeep Acharya - Drexel UniversityPatrick Brennan - Juola & Associates, 301 Grant St, Suite 4300, Pittsburgh, PA 15219, USAPatrick Juola - Juola & Associates, 301 Grant St, Suite 4300, Pittsburgh, PA 15219, USARachel Greenstadt - Drexel UniversityMoshe Kam - New Jersey Institute of Technology
- Publication Details
- Computers & electrical engineering, v 41(C)
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Web of Science ID
- WOS:000352173000013
- Scopus ID
- 2-s2.0-84927731323
- Other Identifier
- 991019346716904721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Hardware & Architecture
- Computer Science, Interdisciplinary Applications
- Engineering, Electrical & Electronic