Anomaly detection is an important problem that has been researched within diverse
research areas and application domains. Many anomaly detection techniques have been …

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

目前, 受生物免疫系统启发而产生的人工免疫系统(Artificial Immune System, AIS) 正在兴起,
它作为计算智能研究的新领域, 提供了一种强大的信息处理和问题求解范式. 该文侧重以AIS …

Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …

In the statistics community, outlier detection for time series data has been studied for
decades. Recently, with advances in hardware and software technology, there has been a …

This survey attempts to provide a comprehensive and structured overview of the existing
research for the problem of detecting anomalies in discrete/symbolic sequences. The …

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 …

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 …

Outliers once upon a time regarded as noisy data in statistics, has turned out to be an
important problem which is being researched in diverse fields of research and application …