Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Stereotype Content Model02:16

Stereotype Content Model

14.0K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.0K
Schemas01:42

Schemas

11.5K
A schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
11.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Comorbidity sequence, sex, and APOE-genotype forecast Alzheimer's disease diagnosis.

Frontiers in medicine·2026
Same author

Leveraging Explainable AI for Early Risk Prediction and Type Classification for Leukemia: Insights Using Clinical Data From Pakistan.

IEEE journal of biomedical and health informatics·2025
Same author

Top-k sentiment analysis over spatio-temporal data.

PeerJ. Computer science·2024
Same author

A hybrid dependency-based approach for Urdu sentiment analysis.

Scientific reports·2023
Same author

Less is more: Efficient behavioral context recognition using Dissimilarity-Based Query Strategy.

PloS one·2023
Same author

Interpretable Differential Diagnosis of Non-COVID Viral Pneumonia, Lung Opacity and COVID-19 Using Tuned Transfer Learning and Explainable AI.

Healthcare (Basel, Switzerland)·2023

Related Experiment Video

Updated: Jun 9, 2025

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

8.9K

Enhancing smartphone security with human centric bimodal fallback authentication leveraging sensors.

Asma Ahmad Farhan1, Amna Basharat2, Nasser Allheeib3

  • 1National University of Computers and Emerging Sciences, FAST, Lahore, 54000, Pakistan.

Scientific Reports
|October 21, 2024
PubMed
Summary

This study introduces a novel smartphone authentication method combining dynamic security questions and finger movement patterns. This bi-model approach enhances security by verifying users through behavioral data and inertial sensor readings.

Keywords:
AuthenticationBehavioral bio-metricsFallbackSensors

More Related Videos

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K

Related Experiment Videos

Last Updated: Jun 9, 2025

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

8.9K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.6K

Area of Science:

  • Computer Science
  • Cybersecurity
  • Human-Computer Interaction

Background:

  • Smartphones contain sensitive personal data, requiring advanced security measures.
  • Existing authentication methods may not offer sufficient protection against sophisticated threats.

Purpose of the Study:

  • To develop and evaluate a lightweight bi-model fallback authentication system for smartphones.
  • To enhance user data protection by combining dynamic security questions with inertial measurement unit (IMU) data.

Main Methods:

  • Dynamic security questions were generated based on user smartphone behavior (calls, SMS, app usage, etc.).
  • Finger movement patterns were captured using accelerometer, gyroscope, gravity sensor, and magnetometer (IMUs).
  • A bi-model system combined question responses and IMU data for authentication, tested with 24 participants over 28 days.

Main Results:

  • Dynamic security questions, particularly those based on call, SMS, and app usage, showed high accuracy.
  • Integrating IMUs significantly boosted authentication accuracy from a maximum of to .
  • The True Positive Rate improved from 0.79 to 0.99, demonstrating enhanced detection capabilities.

Conclusions:

  • The proposed lightweight bi-model fallback authentication is effective for smartphone security.
  • Combining dynamic security questions with IMU data offers a robust and improved user authentication solution.
  • This technique presents a promising advancement in securing personal information on mobile devices.