.png){kind=icon}
Return
ActID: An efficient framework for activity sensor based user identification
.png){kind=icon}
OA
AI
DOI：10.1016/j.cose.2021.102319.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Identification is the core of any authentication protocol design as the purpose of the authentication is to verify the user's identity. The efficient establishment and verification of identity remain a big challenge. Recently, biometrics-based identification algorithms gained popularity as a means of identifying individuals using their unique biological characteristics. In this paper, we propose a novel and efficient identification framework, ActID, which can identify a user based on his/her hand motion while walking. ActID not only selects a set of high-quality features based on Optimal Feature Evaluation and Selection and Correlation based Feature Selection algorithms but also includes a novel sliding window based voting classifier. Therefore, it achieves several important design goals for gait authentication based on resource-constrained devices, including lightweight and real-time classification, high identification accuracy, a minimum number of sensors, and a minimum amount of data collected. Performance evaluation shows that ActID is cost-effective and easily deployable, satisfies real-time requirements, and achieves a high identification accuracy of 100%. (c) 2021 Elsevier Ltd. All rights reserved.
Keywords:
Wearables
Sensors
Biometric
Identification
Classification
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
C
IF:
5.4
Papers:
4.6K
Citations:
1.4W
Organization
Cited Papers
Ge-GaAs (110) Interface: A Self-Consistent Calculation of Interface States and Electronic Structure
PREAI
ShareSaveSecuring Mobile Healthcare Data: A Smart Card Based Cancelable Finger-Vein Bio-Cryptosystem.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAIShareSaveFlowering and Growth of Phalaenopsis Orchids following Growth Retardant ApplicationsHortScience
OAAI
HortScienceIF0
OAAIShareSaveShareSaveWearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang TransformSENSORSOAAI
SENSORSIF3.5
OAAIShareSaveAnalyses for oxygen vacancies in (Na,K)NbO3-series piezoelectric ceramics by soft x-ray emission spectroscopyAIP AdvancesOAAI
AIP AdvancesIF0
OAAIShareSave
View more