Open Access
ARTICLE
The Design and Implementation of a Multidimensional and Hierarchical Web Anomaly Detection System
Jianfeng Guan*, Jiawei Li, Zhongbai Jiang
* P.O. Box 202, Beijing University of Posts and Telecommunications, Haidian District, Beijing, 100876, China.
State Key Laboratory of Networking and Switching Technology
Beijing University of Posts Telecommunications, Beijing, 100876, China
jfguan@bupt.edu.cn, ljwemls@gmail.com, zbjiang@bupt.edu.cn
* Corresponding Author: Jianfeng Guan,
Intelligent Automation & Soft Computing 2019, 25(1), 131-141. https://doi.org/10.31209/2018.100000050
Abstract
The traditional web anomaly detection systems face the challenges derived from the
constantly evolving of the web malicious attacks, which therefore result in high false
positive rate, poor adaptability, easy over-fitting, and high time complexity. Due to
these limitations, we need a new anomaly detection system to satisfy the
requirements of enterprise-level anomaly detection. There are lots of anomaly
detection systems designed for different application domains. However, as for web
anomaly detection, it has to describe the network accessing behaviours characters
from as many dimensions as possible to improve the performance. In this paper we
design and implement a Multidimensional and Hierarchical Web Anomaly Detection
System (MHWADS) with the objectives to provide high performance, low latency,
multi-dimension and adaptability. MHWADS calculates the statistical characteristics,
and constructs the corresponding statistical model, detects the behaviour
characteristics to generate the multidimensional correlation eigenvectors, and
adopts several classifications to build an ensemble model. The system performance
is evaluated based on realistic dataset, and the experimental results show that
MHWADS yields substantial improvements than the previous single model. More
important, by using 2-fold Stacking as the ensemble architecture, the detection
precision and recall are 0.99988 and 0.99647, respectively.
Keywords
Cite This Article
J. Guan, J. Li and Z. Jiang, "The design and implementation of a multidimensional and hierarchical web anomaly detection system,"
Intelligent Automation & Soft Computing, vol. 25, no.1, pp. 131–141, 2019. https://doi.org/10.31209/2018.100000050