How accurately can you identify me? Abdallah El Ali ⋆ , Liam Ashby ⨱, Andrew M. Webb ⋆ , Robert Zwitser ⨱, Pablo Cesar ⋆⨢ ⋆ Centrum Wiskunde & Informatica, ⨱ University of Amsterdam, ⨢ TU Delft Abdallah El Ali [email protected] www.abdoelali.com Abdallah El Ali, Liam Ashby, Andrew M. Webb, Robert Zwitser, Pablo Cesar. Uncovering Perceived Identification Accuracy of In-Vehicle Biometric Sensing. In AutomotiveUI 2019. Utrecht, NL Uncovering Perceived Identification Accuracy of In-Vehicle Biometric Sensing Why study this? ▸ My touches on a smartphone My typing on a computer keyboard My mouse movements My hand sweat My breathing My sleeping pa8erns My heartbeat My hand gestures My brain ac9vity My footprints My physical ac9vity My facial expressions My interac9on pa8erns with an IVIS My posture My walking style My driving style My SMS messages My media watching history My loca9ons on a given day My smartphone app usage My media listening history My signature My hands My wri9ng style My handwri9ng My ears My smell My fingerprints My face My gene9c makeup My eyes My teeth My voice “Please group the cards into distinct sets by how accurately someone can identify you using only the feature stated on a card.” N = 11 (6f, 5m) - Biometric techniques can make vehicles safer to drive (e.g., drowsiness detection), protect them against theft (e.g., authentication), provide higher cost efficiency (e.g., rewarding good driver profiles), or provide personalized in-car experiences (e.g., route personalization). - Privacy-personalization paradox: consumers who value information transparency are also less likely to participate in personalization. ➞ Need for understanding trade-off of sharing personal biometric data for in-vehicle user benefits. - My muscle movements - My personality - My eye gaze patterns - My driving route - My company in a vehicle - My body temperature - My eating style - My saliva ▸ Future / missed cards Closed card sorting website RQ: How well do users perceive their physical, behavioral and physiological features can personally identify them? Analysis: Ward’s hierarchical agglomerative clustering (k=6) ▸

How accurately can you identify me? · Abdallah El Ali [email protected] Abdallah El Ali, Liam Ashby, Andrew M. Webb, Robert Zwitser, Pablo Cesar. Uncovering Perceived Identiﬁcation Accuracy

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How accurately can you identify me?

Abdallah El Ali ⋆, Liam Ashby ⨱, Andrew M. Webb ⋆, Robert Zwitser ⨱, Pablo Cesar ⋆⨢⋆ Centrum Wiskunde & Informatica, ⨱ University of Amsterdam, ⨢ TU Delft

Abdallah El [email protected]

Abdallah El Ali, Liam Ashby, Andrew M. Webb, Robert Zwitser, Pablo Cesar. Uncovering Perceived Identification Accuracy of In-Vehicle Biometric Sensing. In AutomotiveUI 2019. Utrecht, NL

Uncovering Perceived Identification Accuracy of In-Vehicle Biometric Sensing

Why study this?

▸

Mytouchesonasmartphone

Mytypingonacomputerkeyboard

Mymousemovements

Myhandsweat

Mybreathing

Mysleepingpa8erns

Myheartbeat

Myhandgestures

Mybrainac9vity

Myfootprints

Myphysicalac9vity

Myfacialexpressions

Myinterac9onpa8ernswithan

IVIS

Myposture

Mywalkingstyle

Mydrivingstyle

MySMSmessages

Mymediawatchinghistory

Myloca9onsonagivenday

Mysmartphoneappusage

Mymedialisteninghistory

Mysignature

Myhands

Mywri9ngstyle

Myhandwri9ng

Myears

Mysmell

Myfingerprints

Myface

Mygene9cmakeup

Myeyes

Myteeth

Myvoice

“Please group the cards into distinct sets by how accurately someone can identify you using only the feature stated on a card.”

N = 11 (6f, 5m)

- Biometric techniques can make vehicles safer to drive (e.g., drowsiness detection), protect them against theft (e.g., authentication), provide higher cost efficiency (e.g., rewarding good driver profiles), or provide personalized in-car experiences (e.g., route personalization).

- Privacy-personalization paradox: consumers who value information transparency are also less likely to participate in personalization.

➞ Need for understanding trade-off of sharing personal biometric data for in-vehicle user benefits.

- My muscle movements- My personality- My eye gaze patterns- My driving route- My company in a vehicle- My body temperature- My eating style- My saliva

▸

Future / missed cards Closed card sorting website

RQ: How well do users perceive their physical, behavioral and physiological features can personally identify them?

Analysis: Ward’s hierarchical agglomerative clustering (k=6)

▸