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Automated Measurements of Cross-Device Tracking

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Information and Operational Technology Security Systems (IOSec 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11398))

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Abstract

Although digital advertising fuels much of today’s free Web, it typically do so at the cost of online users’ privacy, due to continuous tracking and leakage of users’ personal data. In search for new ways to optimize effectiveness of ads, advertisers have introduced new paradigms such as cross-device tracking (CDT), to monitor users’ browsing on multiple screens, and deliver (re)targeted ads in the appropriate screen. Unfortunately, this practice comes with even more privacy concerns for the end-user. In this work, we design a methodology for triggering CDT by emulating realistic browsing activity of end-users, and then detecting and measuring it by leveraging advanced machine learning tools.

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Notes

  1. 1.

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Acknowledgments

This research has received funding from the European Union’s Horizon 2020 research and innovation programme under Grand Agreement No. 700378 (project CIPSEC) and the Marie Sklodowska-Curie Grand Agreement No. 690972 (project PROTASIS). This paper reflects only the authors’ view and the Agency is not responsible for any use that may be made of the information it contains.

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Authors and Affiliations

  1. FORTH, Heraklion, Greece

    Konstantinos Solomos, Panagiotis Ilia & Sotiris Ioannidis

  2. Telefonica Research, Barcelona, Spain

    Nicolas Kourtellis

Authors
  1. Konstantinos Solomos
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  2. Panagiotis Ilia
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  3. Sotiris Ioannidis
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  4. Nicolas Kourtellis
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Corresponding author

Correspondence to Konstantinos Solomos .

Editor information

Editors and Affiliations

  1. University of Patras, Patras, Greece

    Apostolos P. Fournaris

  2. University of Patras, Patras, Greece

    Konstantinos Lampropoulos

  3. Advanced Network Architectures Lab, Barcelona, Spain

    Eva Marín Tordera

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Solomos, K., Ilia, P., Ioannidis, S., Kourtellis, N. (2019). Automated Measurements of Cross-Device Tracking. In: Fournaris, A., Lampropoulos, K., Marín Tordera, E. (eds) Information and Operational Technology Security Systems. IOSec 2018. Lecture Notes in Computer Science(), vol 11398. Springer, Cham. https://doi.org/10.1007/978-3-030-12085-6_7

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  • DOI: https://doi.org/10.1007/978-3-030-12085-6_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-12084-9

  • Online ISBN: 978-3-030-12085-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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