mlsanityData to 7 Oct 2026

IJCB 2022 Mobile Behavioral Biometrics Competition (MobileB2C)

arXiv 2210.03072 ↗First posted 6 Oct 2022cs.CV cs.HCcited by 5

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Abstract (arXiv)

This paper describes the experimental framework and results of the IJCB 2022 Mobile Behavioral Biometrics Competition (MobileB2C). The aim of MobileB2C is benchmarking mobile user authentication systems based on behavioral biometric traits transparently acquired by mobile devices during ordinary Human-Computer Interaction (HCI), using a novel public database, BehavePassDB, and a standard experimental protocol. The competition is divided into four tasks corresponding to typical user activities: keystroke, text reading, gallery swiping, and tapping. The data are composed of touchscreen data and several background sensor data simultaneously acquired. "Random" (different users with different devices) and "skilled" (different user on the same device attempting to imitate the legitimate one) impostor scenarios are considered. The results achieved by the participants show the feasibility of user authentication through behavioral biometrics, although this proves to be a non-trivial challenge. MobileB2C will be established as an on-going competition.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 13 of its 32 references that are in the map. First posted on arXiv 6 Oct 2022.

Builds on

13 of 32 references.

References · 13

  1. 2020BioTouchPass2: Touchscreen Password Biometrics Using Time-Aligned Recurrent Neural Networkscited by 19
  2. 2021TypeNet: Deep Learning Keystroke Biometricscited by 19
  3. 2021A Survey of Privacy Vulnerabilities of Mobile Device Sensorscited by 18
  4. 2020Smartphone Sensors for Modeling Human-Computer Interaction: General Outlook and Research Datasets for User Authenticationcited by 17
  5. 2021SVC-onGoing: Signature Verification Competitioncited by 17
  6. 2022ECG Biometric Recognition: Review, System Proposal, and Benchmark Evaluationcited by 15
  7. 2022Exploring Transformers for Behavioural Biometrics: A Case Study in Gait Recognitioncited by 13
  8. 2015Learning Human Identity from Motion Patternscited by 9
  9. 2022BehavePassDB: Public Database for Mobile Behavioral Biometrics and Benchmark Evaluationcited by 8
  10. 2019Actions Speak Louder Than (Pass)words: Passive Authentication of Smartphone Users via Deep Temporal Featurescited by 7
  11. 2022Mobile Behavioral Biometrics for Passive Authenticationcited by 4
  12. 2015Exploring Ways To Mitigate Sensor-Based Smartphone Fingerprintingcited by 3
1 more
  1. 2021Benchmarking and challenges in security and privacy for voice biometricscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 0; 2026: 1.

5 papers.