A method for anomaly detection is introduced in which" normal" is defined by short-range
correlations in a process' system calls. Initial experiments suggest that the definition is stable …

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 …

We present new results on a distributable change-detection method inspired by the natural
immune system. A weakness in the original algorithm was the exponential cost of generating …

This paper examines some of the theoretical foundations of the distributable change
detection method introduced by S. Forrest et al.(1994), including fundamental bounds on …

Self-organizing diagnosis is studied by applying the dynamic propagation of active states
derived from the concept of an immune network. The proposed model is a mutual vote …

A new information processing architecture is extracted from immune systems. By focusing on
informational features of the immune system (ie specificity, diversity, tolerance, and …

We first compare the paradigm of the immunity-based system with other biological paradigm
such as neural networks and genetic algorithm. We review studies of the immunity-based …

A new information processing architecture is extracted from the immune system. By focusing
on informational features of the immune system (ie specificity, diversity, tolerance, and …

Based on some features of the immune system (the selection-based mechanism compatible
with Edelman's selectionist principle, self/nonself-reference and negative/positive selection) …

The concept-well known to practitioners-of moving average is recalled, and the one of
adaptive moving average summarized. Then a new algorithm is introduced, and it is shown …