Kid on the phone! Toward automatic detection of children on mobile devices

Toan Nguyen, Aditi Roy, Nasir Memon

Research output: Contribution to journalArticlepeer-review


Studies have shown that children can be exposed to smart devices at a very early age. This has important implications on research in children–computer interaction, children online safety and early education. Many systems have been built based on such research. In this work, we present multiple techniques to automatically detect the presence of a child on a smart device, which could be used as the first step on such systems. Our methods distinguish children from adults based on behavioral differences while operating a touch-enabled modern computing device. Behavioral differences are extracted from data recorded by the touchscreen and built-in sensors. To evaluate the effectiveness of the proposed methods, a new data set has been created from 50 children and adults who interacted with off-the-shelf applications on smart phones. Results show that it is possible to achieve 99% accuracy and less than 0.5% error rate after 8 consecutive touch gestures using only touch information or 5 s of sensor reading. If information is used from multiple sensors, then only after 3 gestures, similar performance could be achieved.

Original languageEnglish (US)
Pages (from-to)334-348
Number of pages15
JournalComputers and Security
StatePublished - Jul 2019


  • Adults
  • Age group
  • Behavior
  • Children
  • Mobile devices
  • Online safety
  • Parental control

ASJC Scopus subject areas

  • General Computer Science
  • Law


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