research-article

XRec: Behavior-Based User Recognition Across Mobile Devices

Authors:

Patrick TagueAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 1, Issue 3

Article No.: 111, Pages 1 - 26

https://doi.org/10.1145/3130975

Published: 11 September 2017 Publication History

Abstract

As smartphones and tablets become increasingly prevalent, more customers have multiple devices. The multi-user, multi-device interactions inspire many problems worthy of investigation, among which recognizing users across devices has significant implications on recommendation, advertising and user experience. Unlike the binary classification problem in user identification on a single device, cross-device user recognition is essentially a set partition problem. The app back-end aims to divide user activities on devices hosting the app into groups each associated with one user. In this paper, we present XRec which leverages user behavioral patterns, namely when, where and how a user uses the app, to achieve the recognition. To address the user-device partition problem, we propose a classification-plus-refinement algorithm. To validate our approach, we conduct a field study with an Android app. We instrument the app to collect usage data from real users. We provide proof-of-concept experimental results to demonstrate how XRec can provide added value to mobile apps, with the ability to correctly match a user across multiple devices with 70% recall and 90% precision.

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Cited By

Zhang ABernstein MKarger DAckerman M(2024)Form-From: A Design Space of Social Media SystemsProceedings of the ACM on Human-Computer Interaction10.1145/36410068:CSCW1(1-47)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3641006
Zhang XOu ZYang Z(2023)FedMPT: Federated Learning for Multiple Personalized Tasks Over Mobile ComputingIEEE Transactions on Network Science and Engineering10.1109/TNSE.2023.3246463(1-15)Online publication date: 2023
https://doi.org/10.1109/TNSE.2023.3246463
Li QWang J(2023)FedAPI: Privacy-preserving Multi-end Adaptive Personal Identification via Federated Learning2023 International Conference on Artificial Intelligence of Things and Systems (AIoTSys)10.1109/AIoTSys58602.2023.00051(198-205)Online publication date: 19-Oct-2023
https://doi.org/10.1109/AIoTSys58602.2023.00051
Show More Cited By

Index Terms

XRec: Behavior-Based User Recognition Across Mobile Devices

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 1, Issue 3

September 2017

2023 pages

EISSN:2474-9567

DOI:10.1145/3139486

Issue’s Table of Contents

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 11 September 2017

Published in IMWUT Volume 1, Issue 3

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Cited By

Zhang ABernstein MKarger DAckerman M(2024)Form-From: A Design Space of Social Media SystemsProceedings of the ACM on Human-Computer Interaction10.1145/36410068:CSCW1(1-47)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3641006
Zhang XOu ZYang Z(2023)FedMPT: Federated Learning for Multiple Personalized Tasks Over Mobile ComputingIEEE Transactions on Network Science and Engineering10.1109/TNSE.2023.3246463(1-15)Online publication date: 2023
https://doi.org/10.1109/TNSE.2023.3246463
Li QWang J(2023)FedAPI: Privacy-preserving Multi-end Adaptive Personal Identification via Federated Learning2023 International Conference on Artificial Intelligence of Things and Systems (AIoTSys)10.1109/AIoTSys58602.2023.00051(198-205)Online publication date: 19-Oct-2023
https://doi.org/10.1109/AIoTSys58602.2023.00051
Li QYu ZYao LGuo B(2022)RLTIR: Activity-Based Interactive Person Identification via Reinforcement Learning TreeIEEE Internet of Things Journal10.1109/JIOT.2021.31040249:6(4464-4475)Online publication date: 15-Mar-2022
https://doi.org/10.1109/JIOT.2021.3104024
Yu ZLi QYang FGuo B(2021)Human–machine computingCCF Transactions on Pervasive Computing and Interaction10.1007/s42486-020-00051-1Online publication date: 5-Jan-2021
https://doi.org/10.1007/s42486-020-00051-1
Liang YSamtani SGuo BYu Z(2020)Behavioral Biometrics for Continuous Authentication in the Internet-of-Things Era: An Artificial Intelligence PerspectiveIEEE Internet of Things Journal10.1109/JIOT.2020.30040777:9(9128-9143)Online publication date: Sep-2020
https://doi.org/10.1109/JIOT.2020.3004077
Sugrim SLiu CLindqvist J(2019)Recruit Until It FailsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33512623:3(1-26)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1145/3351262
Larsen-Ledet IKorsgaard H(2019)Territorial Functioning in Collaborative WritingComputer Supported Cooperative Work10.1007/s10606-019-09359-828:3-4(391-433)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s10606-019-09359-8
Zeng MGao HYu TMengshoel OLangseth HLane ILiu XKunze KBalan RLee YBeigl MPeiris R(2018)Understanding and improving recurrent networks for human activity recognition by continuous attentionProceedings of the 2018 ACM International Symposium on Wearable Computers10.1145/3267242.3267286(56-63)Online publication date: 8-Oct-2018
https://dl.acm.org/doi/10.1145/3267242.3267286

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