Hidden Markov Model Attacks

Hidden Markov Model Attacks is a side-channel attack method that exploits the probabilistic temporal dependencies between a device's observable leakage and its internal hidden states by modeling the leakage process as a Hidden Markov Model to infer secret cryptographic keys.

64

Publications

3.3K

Citations

207

Authors

103

Institutions

Publications per year

2017–2026

33

Authors

207

  1. AJ
    Anupam Joshi

    University of Maryland, Baltimore County, United States

    4 publications · 150 citations

    4

    h-index

  2. SM
    Sudip Mittal

    University of Maryland, Baltimore County, United States

    4 publications · 150 citations

    4

    h-index

  3. MR
    Matthew Roughan

    The University of Adelaide, Australia

    2 publications · 23 citations

    2

    h-index

  4. PJ
    Panos J. Antsaklis

    University of Notre Dame, United States

    2 publications · 255 citations

    2

    h-index

  5. SN
    Sandeep Narayanan

    Centre National de la Recherche Scientifique, France

    2 publications · 28 citations

    2

    h-index

1–5 of 207

Venues

  1. IEEE Internet of Things Journal

    2 publications · 61 citations

    2

    h-index

  2. IEEE Transactions on Automatic Control

    2 publications · 438 citations

    2

    h-index

  3. IEEE Transactions on Network Science and Engineering

    NSE · 2 publications · 84 citations

    2

    h-index

  4. IEEE Network

    2 publications · 82 citations

    2

    h-index

  5. arXiv (Cornell University)

    Repository · 2 publications · 42 citations

    2

    h-index

1–5