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Human-Centric Machine Learning: The Role of Users in the Development of IoT Device Identification and Vulnerability Assessment

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HCI for Cybersecurity, Privacy and Trust (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14045))

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Abstract

Big data, Artificial Intelligence (AI), and Machine Learning (ML) have recently been posited as both a challenge and an opportunity for Human-Computer Interaction (HCI) research. Researchers and practitioners have also expressed concern about these systems’ potential for favouritism, lack of transparency, and impartiality. We focus on the real-world utilization of various IoT devices and systems, communications technologies, and privacy and security considerations specific to the industry. We found that while the survey responses did validate some of our initial assumptions about privacy and security needs at Canadian ports, responses to the survey questions on IoT device and system usage and privacy and security needs were diverse, indicating an initial requirement for flexibility in UX design.

A. A. Ghorbani—These authors contributed equally to this work.

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Acknowledgments

The authors graciously acknowledge the support from the Canadian Institute for Cybersecurity (CIC), the funding support from the National Research Council of Canada (NRC) through the AI for Logistics collaborative program, the NSERC Discovery Grant (no. RGPIN 231074), and Tier 1 Canada Research Chair Dr. Ghorbani.

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Authors and Affiliations

  1. Faculty of Computer Science, University of New Brunswick, Fredericton, NB, Canada

    Priscilla Kyei Danso, Alireza Zohourian, Euclides Carlos Pinto Neto, Sajjad Dadkhah & Ali A. Ghorbani

  2. National Research Council (NRC), Fredericton, NB, Canada

    Heather Molyneaux

  3. Information Technology Services, Port of Halifax, Halifax, NS, Canada

    Derrick Whalen

Authors
  1. Priscilla Kyei Danso
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Correspondence to Priscilla Kyei Danso .

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  1. San Jose State University, San Jose, CA, USA

    Abbas Moallem

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Danso, P.K. et al. (2023). Human-Centric Machine Learning: The Role of Users in the Development of IoT Device Identification and Vulnerability Assessment. In: Moallem, A. (eds) HCI for Cybersecurity, Privacy and Trust. HCII 2023. Lecture Notes in Computer Science, vol 14045. Springer, Cham. https://doi.org/10.1007/978-3-031-35822-7_40

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  • DOI: https://doi.org/10.1007/978-3-031-35822-7_40

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