Novelty detection is the identification of new or unknown data or signal that a machine
learning system is not aware of during training. Novelty detection is one of the fundamental …

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 …

The area of metaheuristics has grown immensely in the past two decades as a solution to
real-world optimisation problems. They are able to perform well in situations where exact …

A method is introduced for detecting intrusions at the level of privileged processes. Evidence
is given that short sequences of system calls executed by running processes are a good …

Intrusion detection based upon computational intelligence is currently attracting
considerable interest from the research community. Characteristics of computational …

We examine several host-based anomaly detection systems and study their security against
evasion attacks. First, we introduce the notion of a mimicry attack, which allows a …

A comprehensive introduction to new approaches in artificial intelligence and robotics that
are inspired by self-organizing biological processes and structures. New approaches to …

An artificial immune system (ARTIS) is described which incorporates many properties of
natural immune systems, including diversity, distributed computation, error tolerance …

The immune system is a remarkable information processing and self learning system that
offers inspiration to build artificial immune system (AIS). The field of AIS has obtained a …

Current intrusion detection systems (IDS) examine all data features to detect intrusion or
misuse patterns. Some of the features may be redundant or contribute little (if anything) to …