Data Reduction for Network Forensics Using Manifold Learning

@article{Peng2010DataRF,
  title={Data Reduction for Network Forensics Using Manifold Learning},
  author={Tao Peng and Xiaosu Chen and Huiyu Liu and Kai Chen},
  journal={2010 2nd International Workshop on Database Technology and Applications},
  year={2010},
  pages={1-5}
}
In network forensic system, there are huge amount of data should be processed, and the data contains redundant and noisy features causing slow training and testing process, high resource consumption as well as poor detection rate. In this paper, a schema is proposed to reduce the data of the forensics using manifold learning. Manifold learning is a popular recent approach to nonlinear dimensionality reduction. Algorithms for this task are based on the idea that the dimensionality of many data… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-8 of 8 references

An Efficient Feature Selection Algorithm Toward Building Lightweight Intrusion Detection System

  • CHEN You SHEN Hua-Wei LI Yang CHENG Xue-Qi
  • SIAM Journal on Scientific Computing
  • 2004

Web Security, Privacy & Commerce, 2nd Edition

  • Simson Garfinkel
  • http://www.oreillynet.com/pub/a/network
  • 2002
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