mlsanityData to 14 Oct 2026

Machine Learning Algorithms In User Authentication Schemes

arXiv 2110.07826 ↗First posted 15 Oct 2021cs.CR cs.AIcited by 11

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Abstract (arXiv)

In the past two decades, the number of mobile products being created by companies has grown exponentially. However, although these devices are constantly being upgraded with the newest features, the security measures used to protect these devices has stayed relatively the same over the past two decades. The vast difference in growth patterns between devices and their security is opening up the risk for more and more devices to easily become infiltrated by nefarious users. Working off of previous work in the field, this study looks at the different Machine Learning algorithms used in user authentication schemes involving touch dynamics and device movement. This study aims to give a comprehensive overview of the current uses of different machine learning algorithms that are frequently used in user authentication schemas involving touch dynamics and device movement. The benefits, limitations, and suggestions for future work will be thoroughly discussed throughout this paper.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 2 of its 27 references that are in the map. First posted on arXiv 15 Oct 2021.

Builds on

2 of 27 references.

References · 2

  1. 2021Applications of Recurrent Neural Network for Biometric Authentication & Anomaly Detectioncited by 15
  2. 2019MultiLock: Mobile Active Authentication based on Multiple Biometric and Behavioral Patternscited by 8

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Cited by year

Citing papers per year: 2022: 7; 2023: 4.

11 papers.

  1. 2022Hold On and Swipe: A Touch-Movement Based Continuous Authentication Schema based on Machine Learningcited by 12
  2. 2022Human Activity Recognition models using Limited Consumer Device Sensors and Machine Learningcited by 8
  3. 2022A Close Look into Human Activity Recognition Models using Deep Learningcited by 8
  4. 2022Using Deep Learning to Detecting Deepfakescited by 6
  5. 2022A Robust Framework for Deep Learning Approaches to Facial Emotion Recognition and Evaluationcited by 3
  6. 2023Deepfake Detection Analyzing Hybrid Dataset Utilizing CNN and SVMcited by 3
  7. 2023Leveraging Deep Learning Approaches for Deepfake Detection: A Reviewcited by 2
  8. 2023Hybrid Deepfake Detection Utilizing MLP and LSTMcited by 1
  9. 2023Your Identity is Your Behavior -- Continuous User Authentication based on Machine Learning and Touch Dynamicscited by 1
  10. 2022Exploration of Machine Learning Classification Models Used for Behavioral Biometrics Authenticationcited by 0
  11. 2022Mitigating Presentation Attack using DCGAN and Deep CNNcited by 0