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

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 …

Susceptible (S)–exposed (E)–infectious (I)–quarantined (Q)–recovered (R) model for the
transmission of malicious objects in computer network is formulated. Thresholds, equilibria …

The natural world is enormous, dynamic, incredibly diverse, and highly complex. Despite the
inherent challenges of surviving in such a world, biological organisms evolve, self-organize …

Artificial Immune Systems (AIS) are computational paradigms that belong to the
computational intelligence family and are inspired by the biological immune system. During …

An e-epidemic SIRS (susceptible–infectious–recovered–susceptible) model for the fuzzy
transmission of worms in computer network is formulated. We have analyzed the …

This paper presents a methodology that designs a fault detection Artificial Immune System
(AIS) based on immune theory. The fault detection is a challenging problem due to …

Artificial immune systems are a kind of new computational intelligence methods which draw
inspiration from the human immune system. Most immune system inspired optimization …

In this paper, we present a heuristic inspired on the T‐Cell model of the immune system (ie
an artificial immune system). The proposed approach (called T‐Cell) is used for solving …

This paper proposes a new negative selection algorithm method that uses chaotic maps for
parameter selection. This has been done by using of chaotic number generators each time a …