Artificial Immune Systems (AIS) have long been used in the field of computer security and especially in Intrusion Detection systems. Intrusion detection based on AISs falls into two main categories. The first generation of AIS is inspired from adaptive immune reactions but, the second one which is called danger theory focuses on both adaptive and innate reactions to build a more biologically-re...

The self-non-self theory has dominated immunology since the 1950s. In the 1990s, Matzinger and her colleagues suggested a new, competing theory, called the "danger theory." This theory has provoked mixed acclaim: enthusiasm and criticism. Here we assess the danger theory vis-à-vis recent experimental data on innate immunity, transplantation, cancers and tolerance to foreign entities, and try to...

The traditional immune algorithm (IA) is based on a self–nonself biological immunity mechanism. Recently, a novel immune theory called the danger model theory has provided more suitable biological information for data handling compared with the self–nonself mechanism. According to the danger model theory and based on past experiences of the genetic and artificial IA, we present the Danger Model...

Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas aro...

Within immunology, new theories are constantly being proposed that challenge current ways of thinking. These include new theories regarding how the immune system responds to pathogenic material. This conceptual paper takes one relatively new such theory: the Danger theory, and explores the relevance of this theory to the application domain of web mining. Central to the idea of Danger theory is ...