Open AccessResearch on Adaptive ISOMAP Algorithm and Application in Intrusion Detection
Author(s) -
Xiang Liu,
Ping Ma,
Gaoming Li
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1607/1/012130
Subject(s) - isomap , intrusion detection system , computer science , robustness (evolution) , pattern recognition (psychology) , artificial intelligence , algorithm , feature extraction , data mining , nonlinear dimensionality reduction , dimensionality reduction , biochemistry , chemistry , gene
In view of the low accuracy and many redundant attributes in the detection algorithms, an intrusion detection algorithm based on adaptive Isomap is proposed. The algorithm uses the sparse representation theory to adaptively select the neighborhood of data points. Then the sparse coefficients are used as the distance weight to improve the data discrimination ability. Finally, the improved isometric feature mapping algorithm is introduced to the intrusion detection as the feature extraction module. The algorithm not only overcomes the difficulty of manual parameter adjustment, but also has strong robustness. Experimental results show that using this method to extract intrusion detection features can effectively improve the detection accuracy, and at the same time improve the detection accuracy of Probe, U2R, R2L.