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Research Article | Open Access |

Hidden Markov Models (HMMs) and Security Applications

Author 1: Rubayyi Alghamdi
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 2 · Published 2016 · Cited by 19

DOI: 10.14569/IJACSA.2016.070205

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Abstract

The Hidden Markov models (HMMs) are statistical models used in various communities and applications. Such applications include speech recognition, mental task classification, biological analysis, and anomaly detection. In hidden Markov models, there are two states: one is a hidden state and the other is an observation state. The purpose of this survey paper is to further the understanding of hidden Markov models, as well as the solutions to the three central problems: evaluation problem, decoding problem and learning problem. In addition, applying HMMs in real world applications such as security and engineering will improve the classification and accuracy for the whole field.

Keywords

Markov model Hidden Markov model HMM Markove model Forward algorithm Viterbi Algorithm Baum-Welch algorithm

How to Cite this Article

Alghamdi, R. (2016). Hidden Markov Models (HMMs) and Security Applications. International Journal of Advanced Computer Science and Applications, 7(2). https://doi.org/10.14569/IJACSA.2016.070205

Alghamdi, Rubayyi. "Hidden Markov Models (HMMs) and Security Applications." International Journal of Advanced Computer Science and Applications, vol. 7, no. 2, 2016, https://doi.org/10.14569/IJACSA.2016.070205.

@article{Alghamdi2016,
  title     = {Hidden Markov Models (HMMs) and Security Applications},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {2},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Rubayyi Alghamdi},
  doi       = {10.14569/IJACSA.2016.070205},
  url       = {https://doi.org/10.14569/IJACSA.2016.070205}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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Volume 17 No. 11, November 2026
Paper Submission Due October 25, 2026
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