Personalisation and privacy in future pervasive display networks
- Submitting institution
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The University of Lancaster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 156987385
- Type
- E - Conference contribution
- DOI
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10.1145/2556288.2557287
- Title of conference / published proceedings
- CHI '14 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- First page
- 2357
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- -
- Year of publication
- 2014
- URL
-
-
- 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
- Yes
- Number of additional authors
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6
- Research group(s)
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G - Pervasive Systems
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This ground-breaking paper proposes a privacy-preserving architecture to safely tailor content on public displays for individual users. It uses beaconed cryptographic tokens and trust relationships with content providers that the viewer already engages with to personalise public display content without pervasive tracking. New metrics for evaluating display personalisation systems are also presented. The work has contributed to 2 PhD theses; enabled a multidisciplinary collaboration exploring cuing human memory (€2.6m RECALL project) along with several other grants (ReCoPs, DiSSC, PACTMAN), and underpins the world’s largest study of display personalisation reported in ACM TOCHI in 2020.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
