Research on Adaptive ISOMAP Algorithm and Application in Intrusion Detection

Abstract

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.