Encrypted traffic classification based on Gaussian mixture models and Hidden Markov Models.
Zhongjiang YaoJingguo GeYulei WuXiaosheng LinRunkang HeYuxiang MaPublished in: J. Netw. Comput. Appl. (2020)
Keyphrases
- hidden markov models
- gaussian mixture model
- sequence classification
- feature vectors
- mixture model
- conditional random fields
- markov models
- speaker recognition
- discriminative training
- visual speech recognition
- speech recognition
- pattern recognition
- classification accuracy
- machine learning
- feature space
- support vector
- feature extraction
- baum welch
- gaussian mixture
- maximum likelihood criterion
- unsupervised learning
- em algorithm
- maximum likelihood
- information retrieval
- probability density function
- density estimation
- automatic speech recognition
- sequential data
- text classification
- dimensionality reduction
- object recognition
- hidden states
- visual speech
- image processing
- feature selection
- minimum classification error