Authentication of Smartphone Users Using Behavioral Biometrics

@article{Alzubaidi2016AuthenticationOS,
  title={Authentication of Smartphone Users Using Behavioral Biometrics},
  author={Abdulaziz Alzubaidi and Jugal Kumar Kalita},
  journal={IEEE Communications Surveys \& Tutorials},
  year={2016},
  volume={18},
  pages={1998-2026}
}
Smartphones and tablets have become ubiquitous in our daily lives. Smartphones, in particular, have become more than personal assistants. These devices have provided new avenues for consumers to play, work, and socialize whenever and wherever they want. Smartphones are small in size, so they are easy to handle and to stow and carry in users' pockets or purses. However, mobile devices are also susceptible to various problems. One of the greatest concerns is the possibility of breach in security… 
Behavioral Biometrics for Continuous Authentication
TLDR
This paper highlights the various continuous authentication methods which can be used to monitor the authors' devices and analyze the current research, proposed framework and mechanisms that can be implemented or have already been implemented.
Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing
TLDR
This work proposes a novel authentication framework, which is based on recognizing the behavioral traits of smartphone users using the embedded sensors of smartphone, such as Accelerometer, Gyroscope and Magnetometer, and provides a platform for carrying out multi-class smart user authentication, which provides different levels of access to a wide range of smartphones users.
Continuous authentication of smartphone users based on activity pattern recognition using passive mobile sensing
TLDR
A novel continuous authentication scheme is proposed for smartphone users, which is based on activity pattern recognition, which recognizes smartphone users on the basis of their physical activity patterns using accelerometer, gyroscope, and magnetometer sensors of smartphone.
Towards Continuous Authentication on Mobile Phones using Deep Learning Models
TLDR
This paper investigates the impact of using both touchscreen-based and sensor-based features in an authentication model using deep learning methods, and trains a three-layer deep network on the combined feature-sets and applied classification for revealing the behavioral characters of users for building an authentication models.
Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing
TLDR
This paper proposes a novel framework to protect sensitive data on smartphones by identifying smartphone users based on their behavioral traits using smartphone embedded sensors, which demonstrates its effectiveness.
Sensor-based Continuous Authentication of Smartphones' Users Using Behavioral Biometrics: A Survey
TLDR
The survey provides an overview of the current state-of-the-art approaches for continuous user authentication using behavioral biometrics captured by smartphones' embedded sensors, including insights and open challenges for adoption, usability, and performance.
Sensor-Based Continuous Authentication of Smartphones’ Users Using Behavioral Biometrics: A Contemporary Survey
TLDR
The survey provides an overview of the current state-of-the-art approaches for continuous user authentication using behavioral biometrics captured by smartphones’ embedded sensors, including insights and open challenges for adoption, usability, and performance.
Behavio2Auth: Sensor-based Behavior Biometric Authentication for Smartphones
TLDR
The problem of unauthorized access is addressed by identifying the user during activities under two considered scenarios: walking and sitting by authenticating users continuously and implicitly based on micro-movements by leveraging the typing activity information on the screen.
AUTHENTICATION OF LEGITIMATE USER S OF SMARTPHONES BASED ON APP USAGE SEQUENCES by ENRIC
Nowadays, it is hard to understand society without smartphones. People may own one or even more of these devices and use them regularly. Consequently, such a trend brings up many security issues,
Continuous Authentication of Smartphone Users via Swipes and Taps Analysis
TLDR
A continuous user authentication system based on user's interaction with the touchscreen in conjunction with micromovements, performed by smartphones at the same time, to reduce the time of impostors' detection.
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 176 REFERENCES
Continuous Authentication on Mobile Devices by Analysis of Typing Motion Behavior
TLDR
By making use of the user’s biometrical behavior while entering text into the smartphone, the approach transparently authenticate the user in an ongoing-fashion and is able to continuously authenticate some users with high precision.
Unobservable Re-authentication for Smartphones
TLDR
This paper proposes a novel biometric-based system to achieve continuous and unobservable re-authentication for smartphones and shows that the system is efficient on smartphones and achieves high accuracy.
Toward Mobile Authentication with Keystroke Dynamics on Mobile Phones and Tablets
  • M. Trojahn, F. Ortmeier
  • Computer Science
    2013 27th International Conference on Advanced Information Networking and Applications Workshops
  • 2013
TLDR
This paper suggests to develop a mixture of a keystroke-based and a handwriting-based authentication method using capacitive displays, and believes that keystroke and handwriting authentication is a possible way for improving the security on mobile devices.
KeySens: Passive User Authentication through Micro-behavior Modeling of Soft Keyboard Interaction
TLDR
This paper proposes a novel passive authentication method, and model the micro-behavior of mobile users’ interaction with their devices’ soft keyboard, showing that the way a user types reflects their unique physical and behavioral characteristics.
Exploring Touch-Screen Biometrics for User Identification on Smart Phones
TLDR
An application for the Android mobile platform is developed to collect data on the way individuals draw lock patterns on a touchscreen, which achieves an average Equal Error Rate (EER) of approximately 10.39%, meaning that lock patterns biometrics can be used for identifying users towards their device, but could also pose a threat to privacy if the users’ biometric information is handled outside their control.
You Are How You Touch: User Verification on Smartphones via Tapping Behaviors
TLDR
This work proposes a non-intrusive user verification mechanism to substantiate whether an authenticating user is the true owner of the smart phone or an impostor who happens to know the pass code.
Know your enemy: the risk of unauthorized access in smartphones by insiders
TLDR
It is found that users are generally concerned about insiders accessing their data on smartphones and a stronger adversarial model must be considered during the design and evaluation of data protection systems and authentication methods for smartphones.
Wave-to-Access: Protecting Sensitive Mobile Device Services via a Hand Waving Gesture
TLDR
A novel application permission granting approach that can be used to protect any sensitive mobile device service via a lightweight hand waving gesture, and is found to be quite effective in preventing the misuse of sensitive resources while imposing only minimal user burden.
Touch Gestures Based Biometric Authentication Scheme for Touchscreen Mobile Phones
TLDR
A novel user authentication scheme based on touch dynamics that uses a set of behavioral features related to touch dynamics for accurate user authentication and optimize the neural network classifier by using Particle Swarm Optimization to deal with variations in users’ usage patterns.
Towards Continuous and Passive Authentication via Touch Biometrics: An Experimental Study on Smartphones
TLDR
This work adopts a continuous and passive authentication mechanism based on a user’s touch operations on the touchscreen that is suitable for smartphones, as it requires no extra hardware or intrusive user interface.
...
1
2
3
4
5
...