Online anomaly detection using dimensionality reduction techniques for HTTP log analysis

@article{Juvonen2015OnlineAD,
  title={Online anomaly detection using dimensionality reduction techniques for HTTP log analysis},
  author={Antti Juvonen and Tuomo Sipola and Timo H{\"a}m{\"a}l{\"a}inen},
  journal={Computer Networks},
  year={2015},
  volume={91},
  pages={46-56}
}
Modern web services face an increasing number of new threats. Logs are collected from almost all web servers, and for this reason analyzing them is beneficial when trying to prevent intrusions. Intrusive behavior often differs from the normal web traffic. This paper proposes a framework to find abnormal behavior from these logs. We compare random projection, principal component analysis and diffusion map for anomaly detection. In addition, the framework has online capabilities. The first two… CONTINUE READING
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