Telemetry Privacy

Telemetry Privacy is a methodological framework within telemetry management that specifies the principles and mechanisms for safeguarding personally identifiable and sensitive operational data collected through remote monitoring systems, distinguishing it from general data privacy approaches by its focus on the unique temporal, spatial, and contextual attributes inherent in telemetry data streams.

4

Publications

504

Citations

8

Authors

3

Institutions

Publications per year

2017–2026

3

Authors

8

  1. JK
    Janardhan Kulkarni

    Duke University, United States

    2 publications · 457 citations

    2

    h-index

  2. BD
    Bolin Ding

    Alibaba Group (United States), United States

    2 publications · 457 citations

    2

    h-index

  3. SY
    Sergey Yekhanin

    Microsoft (United States), United States

    2 publications · 457 citations

    2

    h-index

  4. DS
    Dawn Song

    University of California, Berkeley, United States

    1 publications · 37 citations

    1

    h-index

  5. VN
    Vivek Nair

    University of California, Berkeley, United States

    1 publications · 37 citations

    1

    h-index

1–5 of 8

Venues

  1. arXiv (Cornell University)

    Repository · 1 publications · 265 citations

    1

    h-index

  2. Proceedings on Privacy Enhancing Technologies

    PoPETs · 1 publications · 37 citations

    1

    h-index

  3. Neural Information Processing Systems

    Conference · 1 publications · 192 citations

    1

    h-index

  4. IEEE Security & Privacy

    1 publications · 13 citations

1–4