Sensor Data Privacy

Sensor Data Privacy is a formal construct in the domain of data privacy that specifies the principles and mechanisms governing the protection of personally identifiable and sensitive information collected by sensors in IoT and mobile health systems, distinguishing it from broader privacy frameworks through its focus on real-time, continuous, and context-rich data streams generated by physical and physiological monitoring devices.

193

Publications

10.3K

Citations

716

Authors

296

Institutions

Publications per year

2017–2026

88

Authors

716

  1. MS
    Mani Srivastava

    University of California, Los Angeles, United States

    7 publications · 1.1K citations

    7

    h-index

  2. WP
    Wee Peng Tay

    Nanyang Technological University, Singapore

    6 publications · 164 citations

    6

    h-index

  3. MS
    Meng Sun

    Nanyang Technological University, Singapore

    4 publications · 124 citations

    4

    h-index

  4. BS
    Bo Sheng

    University of Massachusetts Boston, United States

    3 publications · 144 citations

    3

    h-index

  5. RL
    Rongxing Lu

    University of New Brunswick, Canada

    3 publications · 203 citations

    3

    h-index

1–5 of 716

Venues

  1. IEEE Internet of Things Journal

    5 publications · 243 citations

    5

    h-index

  2. Sensors

    4 publications · 101 citations

    4

    h-index

  3. IEEE Sensors Journal

    3 publications · 168 citations

    3

    h-index

  4. Sustainable Cities and Society

    3 publications · 392 citations

    3

    h-index

  5. IEEE Access

    2 publications · 116 citations

    2

    h-index

1–5