Anomaly Dete tion Using Data Mining

On-line Intrusion Detection Using Sequences of System Calls

This thesis investigates the use of anomaly dete tion te hniques for on-line intrusion dete tion. A detailed analysis of methods introdu ed by Forrest et al. is presented and an improved hara terization of intrusions is derived. A novel approa h to integrating this hara terization into an on-line intrusion dete tion system is developed and implemented. Finally, experiments examining the eÆ ien ...

Bayesian Network Anomaly Pattern Dete tion for Disease Outbreaks

Clustering Methods For Spatial Datamining

Abstra t We investigate the use of biased sampling a ording to the density of the dataset, to speed up the operation of general data mining tasks, su h as lustering and outlier dete tion in large multidimensional datasets. In density-biased sampling, the probability that a given point will be in luded in the sample depends on the lo al density of the dataset. We propose a general te hnique for ...

A Distribution Detection Framework for Watermark Analysis

ABSTRACT Many watermarking algorithms have been proposed and studied for their robustness and other properties. But, there has been little e ort is analyzing these algorithms for their vulnerability against dete tion by an adversary. As a general philosophy for robust watermarking the host signal and the watermarked signal are well separated in a statisti al distan e sense. This very nature an ...

Using Program Sli ing to Assist in the Dete tion