Brief Announcement: Deriving Context for Touch Events

Moran Azran, Niv Ben Shabat, Tal Shkolnik, Yossi Oren

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


To quantify the amount of high-level context information which can be derived by observing only a user’s touchscreen interactions, we performed a user study, in which we recorded 160 touch interaction sessions from users running different applications, and then applied both classical machine learning methods and deep learning methods to the results. Our results show that it is possible to derive higher-level user context information based on touch events alone, validating the efficacy of touch injection attacks.

Original languageEnglish
Title of host publicationCyber Security Cryptography and Machine Learning - Second International Symposium, CSCML 2018, Proceedings
EditorsItai Dinur, Shlomi Dolev, Sachin Lodha
PublisherSpringer Verlag
Number of pages4
ISBN (Electronic)978-3-319-94147-9
ISBN (Print)9783319941462
StatePublished - 17 Jun 2018
Event2nd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2018 - Beer-Sheva, Israel
Duration: 21 Jun 201822 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10879 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2018


  • Machine learning
  • Malicious hardware
  • Smart phone

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Brief Announcement: Deriving Context for Touch Events'. Together they form a unique fingerprint.

Cite this