Reconstructing what you said: Text Inference using Smartphone Motion
- Submitting institution
-
The University of East Anglia
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 182621722
- Type
- D - Journal article
- DOI
-
10.1109/TMC.2018.2850313
- Title of journal
- IEEE Transactions on Mobile Computing
- Article number
- 8401706
- First page
- 947
- Volume
- 18
- Issue
- 4
- ISSN
- 1536-1233
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2019
- URL
-
http://www.scopus.com/inward/record.url?scp=85049312695&partnerID=8YFLogxK
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper presents a novel method of text inference on a smartphone using only the accelerometer and gyroscope. Smartphone motion sensors can typically be accessed by an application without the explicit permission of the user. This presents a potential side channel attack that could capture the intercept a range of sensitive information from an unwitting user. The work has inspired further research on user identification using behavioural biometrics in the form of an EPSRC funded grant (EP/S027424/1), a project funded by the Centre for Research and Evidence on Security Threats (CREST) and a self-funded PhD student.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -