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HMOG: New Behavioral Biometric Features for Continuous Authentication of Smartphone Users
[article]
2016
arXiv
pre-print
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We introduce Hand Movement, Orientation, and Grasp (HMOG), a set of behavioral features to continuously authenticate smartphone users. ...
We evaluated authentication and biometric key generation (BKG) performance of HMOG features on data collected from 100 subjects typing on a virtual keyboard. ...
In this paper, we present Hand Movement, Orientation, and Grasp (HMOG), a new set of behavioral biometric features for continuous authentication of smartphone users. ...
arXiv:1501.01199v3
fatcat:nuh4wmu365cyli36tlrhnneeay
HMOG: New Behavioral Biometric Features for Continuous Authentication of Smartphone Users
2016
IEEE Transactions on Information Forensics and Security
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We introduce hand movement, orientation, and grasp (HMOG), a set of behavioral features to continuously authenticate smartphone users. ...
We evaluated authentication and biometric key generation (BKG) performance of HMOG features on data collected from 100 subjects typing on a virtual keyboard. ...
In this paper, we present Hand Movement, Orientation, and Grasp (HMOG), a new set of behavioral biometric features for continuous authentication of smartphone users. ...
doi:10.1109/tifs.2015.2506542
fatcat:fr66f6ddgrb7dpyvunb55t52lu
Relative Attention-based One-Class Adversarial Autoencoder for Continuous Authentication of Smartphone Users
[article]
2022
arXiv
pre-print
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Behavioral biometrics-based continuous authentication is a promising authentication scheme, which uses behavioral biometrics recorded by built-in sensors to authenticate smartphone users throughout the ...
To solve these issues, we propose a relative attention-based one-class adversarial autoencoder for continuous authentication of smartphone users. ...
HMOG dataset: HMOG [34] is a new set of behavioral biometric data for continuous authentication of smartphone users, which contains the Hand Movement, Orientation, and Grasp (HMOG). ...
arXiv:2210.16819v2
fatcat:o3fraaqtinhuzonse5wyyubidy
Deep Learning Approaches for Continuous Authentication Based on Activity Patterns Using Mobile Sensing
2021
Sensors
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To solve these issues, this research introduces a new continuous authentication framework called DeepAuthen, which identifies smartphone users based on their physical activity patterns as measured by the ...
We also conducted a thorough examination of the continuous authentication outcomes, and the results supported the efficacy of our framework. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/s21227519
pmid:34833591
pmcid:PMC8625098
fatcat:wtjhyzrdrjevzj6xe3kftzwvca
Few-Shot Continuous Authentication for Mobile-Based Biometrics
2022
Applied Sciences
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The rapid growth of smartphone financial services raises the need for secure mobile authentication. ...
Continuous authentication is a user-friendly way to strengthen the security of smartphones by implicitly monitoring a user's identity through sessions. ...
Data Availability Statement: This study leveraged two publicly available datasets, the HMOG [37] and BBMAS [38] datasets. The HMOG dataset is downloadable from https://www.cs.wm.edu/~qyang/ ...
doi:10.3390/app122010365
fatcat:c5a4vzkoyrbebcznewkg4jswpe
Hold On and Swipe: A Touch-Movement Based Continuous Authentication Schema based on Machine Learning
[article]
2022
arXiv
pre-print
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This study aims to contribute to this innovative research by evaluating the performance of a multimodal behavioral biometric based user authentication scheme using touch dynamics and phone movement. ...
Behavioral biometrics have been heavily researched as a possible solution to this security deficiency for mobile devices. ...
Balagani, “HMOG: New behavioral biometric features for continuous
[8] N. Siddiqui., R. Dave, and N. ...
arXiv:2201.08564v1
fatcat:teizq3pt7rhoficu5b76nneoza
Exploration of Machine Learning Classification Models Used for Behavioral Biometrics Authentication
[article]
2022
arXiv
pre-print
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Continuing the previous work in this field, this study identifies key Machine Learning algorithms currently being used for behavioral biometric mobile authentication schemes and aims to provide a comprehensive ...
Throughout this paper the benefits, limitations, and recommendations for future work will be discussed. ...
ACKNOWLEDGMENTS Funding for this project has been provided by the University of Wisconsin-Eau Claire's Blugold Fellowship and University of Wisconsin-Eau Claire Computer Science Department's Karlgaard ...
arXiv:2204.09088v1
fatcat:uo2sk5qdzzbgtpmckc5oxterx4
Continuous Mobile User Authentication Using a Hybrid CNN-Bi-LSTM Approach
2023
Computers Materials & Continua
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Behavioral biometrics is introduced by the powerful sensing capabilities of IoT devices such as smart wearables and smartphones, enabling continuous authentication. ...
This paper presents a new continuous passive authentication approach capable of learning the signatures of IoT users utilizing smartphone sensors such as a gyroscope, magnetometer, and accelerometer to ...
[4] used keystrokes dynamics as a behavioral biometrics methodology and utilized a hybrid deep learning model to authenticate users continuously. ...
doi:10.32604/cmc.2023.035173
fatcat:jsoainvovvgmjiwwmnmgfcpwtq
Comparing Machine Learning Classifiers for Continuous Authentication on Mobile Devices by Keystroke Dynamics
2021
Electronics
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Continuous authentication (CA) is the process to verify the user's identity regularly without their active participation. ...
The results show that a small number of key events and measurements can be used to return predictions of user identity. ...
Hand movement, orientation, and grasp (HMOG) is a set of behavioral biometrics for smartphones introduced by Sitová et al. [24] . ...
doi:10.3390/electronics10141622
fatcat:w4oj5ynqpvhltde6cax4pd4kwq
Continuous authentication of smartphone users based on activity pattern recognition using passive mobile sensing
2018
Journal of Network and Computer Applications
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To address these 19 challenges, a novel continuous authentication scheme is presented in this study, which recognizes smartphone 20 users on the basis of their physical activity patterns using accelerometer ...
A series of experiments are performed for user recognition using different machine learning 22 classifiers, where six different activities are analyzed for the multiple locations of smartphone on the user's ...
and gestures as behavioral biometrics for 62 continuous authentication of smartphone users. ...
doi:10.1016/j.jnca.2018.02.020
fatcat:4tu22aitbzaqxjbmpnsbkakhde
DAKOTA: Sensor and Touch Screen-Based Continuous Authentication on a Mobile Banking Application
2021
IEEE Access
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In this paper, we investigate whether it is possible to continuously authenticate users via behavioral biometrics with a certain performance on a mobile banking application. ...
However, this requires active participation of the user and there is continuous authentication during a session. ...
Continuous authentication uses behavioral biometrics, which refer to a specific behavioral pattern to a user [6] . ...
doi:10.1109/access.2021.3063424
fatcat:nwzuwr7h4zbbrohdnxghvzzegq
Data Behind Mobile Behavioural Biometrics – a Survey
2020
IET Biometrics
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In this study, the authors give the reader an overview of mobile device behavioural biometric data and how this data is used in experiments, especially examining papers that introduce new datasets. ...
They further look at the General Data Protection Regulation, and its significance to the scientific research in the field of biometrics. ...
. • Yang et al. [14] -'A Multimodal Data Set for Evaluating Continuous Authentication Performance in Smartphones' and Sitová et al. [52] -'HMOG: New Behavioral Biometric Features for Continuous Authentication ...
doi:10.1049/iet-bmt.2018.5174
fatcat:qmkevrklubhvrfo7yrftlnxvlu
Learning Human Identity From Motion Patterns
2016
IEEE Access
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We present a large-scale study exploring the capability of temporal deep neural networks to interpret natural human kinematics and introduce the first method for active biometric authentication with mobile ...
Our results demonstrate that human kinematics convey important information about user identity and can serve as a valuable component of multi-modal authentication systems. ...
ACKNOWLEDGMENT The authors would like to thank their colleagues Elie Khoury, Laurent El Shafey, Sébastien Marcel and Anupam Das for valuable discussions. ...
doi:10.1109/access.2016.2557846
fatcat:hoypghnlyzge5elj3dic4rwrje
Learning Human Identity from Motion Patterns
[article]
2016
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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We present a large-scale study exploring the capability of temporal deep neural networks to interpret natural human kinematics and introduce the first method for active biometric authentication with mobile ...
Our results demonstrate that human kinematics convey important information about user identity and can serve as a valuable component of multi-modal authentication systems. ...
ACKNOWLEDGMENT The authors would like to thank their colleagues Elie Khoury, Laurent El Shafey, Sébastien Marcel and Anupam Das for valuable discussions. ...
arXiv:1511.03908v4
fatcat:tbtqonhsjvactlakgfp2y2vsz4
Motion ID: Human Authentication Approach
[article]
2023
arXiv
pre-print
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The paper presents two labeled datasets with unlock events: the first features IMU measurements, provided by six users who continuously collected data on six different smartphones for a period of 12 weeks ...
The second one contains 50 hours of IMU data for one specific motion pattern, provided by 101 users. ...
The proposed method not only eliminates all existing obstacles for biometrics, but also reduces the time it takes to authenticate and verify the user (excluding the inference time of the biometric solution ...
arXiv:2302.01751v1
fatcat:jes4yqdwanebnb6x7uapkvmebu
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