Outlier detection has been a very important concept in the realm of data analysis. Recently,
several application domains have realized the direct mapping between outliers in data and …

During the last decade, the field of artificial immune system (A1S) is progressing slowly and
steadily as a branch of computational intelligence (CI). There has been increasing interest in …

Profiling the behavior of programs can be a useful reference for detecting potential
intrusions against systems. This paper presents three anomaly detection techniques for …

Current intrusion detection systems lack the ability to generalize from previously observed
attacks to detect even slight variations of known attacks. This paper describes new process …

Clearly, nature has been very effective in creating organisms that are capable of protecting
themselves against a wide variety of pathogens such as bacteria, fungi, and parasites. The …

This paper presents a technique inspired by the negative selection mechanism of the
immune system that can detect foreign patterns in the complement (nonself) space. In …

Detecting anomalies in time series data is a problem of great practical interest in many
manufacturing and signal processing applications. This paper presents a novelty detection …

This paper describes a real-valued representation for the negative selection algorithm and
its applications to anomaly detection. In many anomaly detection applications, only positive …