Work place: School of Computer Science and Technology of Huazhong University of Science and Technology Wuhan, HuBei 430073, China
E-mail: x_s_chen@mail.hust.edu.cn
Website:
Research Interests: Computer systems and computational processes, Pattern Recognition, Network Architecture, Network Security, Data Mining, Data Structures and Algorithms
Biography
Chen Xiaosu, born in Hubei, china in 1954, Professor and Ph.D. supervisor, His main research interests include computer network, pattern recognition, data mining, network security
By Peng Tao Chen Xiaosu Liu Huiyu Chen Kai
DOI: https://doi.org/10.5815/ijmecs.2011.01.08, Pub. Date: 8 Feb. 2011
In a network forensic system, there are huge amounts of data that should be processed, and the data contains redundant and noisy features causing slow training and testing processes, 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 sets is only artificially high. In this paper, we reduce the forensic data with manifold learning, and test the result of the reduced data.
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