A Feature Selection Method for Large-Scale Network Traffic Classification Based on Spark

@article{Wang2016AFS,
  title={A Feature Selection Method for Large-Scale Network Traffic Classification Based on Spark},
  author={Yong Wang and Wenlong Ke and Xiaoling Tao},
  journal={Information},
  year={2016},
  volume={7},
  pages={6}
}
Currently, with the rapid increasing of data scales in network traffic classifications, how to select traffic features efficiently is becoming a big challenge. Although a number of traditional feature selection methods using the Hadoop-MapReduce framework have been proposed, the execution time was still unsatisfactory with numeral iterative computations during the processing. To address this issue, an efficient feature selection method for network traffic based on a new parallel computing… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-8 of 8 extracted citations

Performance Evaluation for Network Services, Systems and Protocols

Springer International Publishing • 2017
View 8 Excerpts
Highly Influenced

A large-scale filter method for feature selection based on spark

2017 IEEE 4th International Conference on Soft Computing & Machine Intelligence (ISCMI) • 2017

A study on feature selection in big data

2017 International Conference on Computer Communication and Informatics (ICCCI) • 2017

Analysis of feature selection and extraction algorithm for loan data: A big data approach

2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI) • 2017
View 1 Excerpt

An efficient parallel topic-sensitive expert finding algorithm using spark

2016 IEEE International Conference on Big Data (Big Data) • 2016
View 1 Excerpt

References

Publications referenced by this paper.
Showing 1-10 of 21 references

Network Traffic Classification Method Research Based on Cloud Computing and Ensemble Learning

Y. Long
Ph.D. Thesis, Guilin University of Electronic • 2015
View 1 Excerpt

Towards selecting optimal features for flow statistical based network traffic classification

2015 17th Asia-Pacific Network Operations and Management Symposium (APNOMS) • 2015
View 1 Excerpt

An improved method of SVM-BPSO feature selection based on cloud model

J. Z. Li, X. R. Meng, J. Wen
IAES Telkomnika Indones. J. Electr. Eng • 2014
View 1 Excerpt

Data intensive parallel feature selection method study

2014 International Joint Conference on Neural Networks (IJCNN) • 2014
View 1 Excerpt

Similar Papers

Loading similar papers…