Artificial immune systems (AISs) to date have generally been inspired by naive biological metaphors. This has limited the effectiveness of these systems. In this position paper two ways in which AISs could be made more biologically realistic are discussed. We propose that AISs should draw their inspiration from organisms which possess only innate immune systems, and that AISs should employ syst...

Artificial immune systems (AIS) constitute a relatively new area of bio-inspired computing. Biological models of the natural immune system, in particular the theories of clonal selection, immune networks and negative selection, have provided the inspiration for AIS algorithms. Moreover, such algorithms have been successfully employed in a wide variety of different application areas. However, de...

Artificial Immune Systems (AIS) are algorithms inspired by the human immune system. The human immune system is a robust, decentralized, error tolerant and adaptive system. Such properties are highly desirable for the development of novel computer systems. Unlike some other bio-inspired techniques, such as genetic algorithms and neural networks, the field of AIS encompasses a spectrum of algorit...

Artificial Immune System (AIS) is a new intelligent problem-solving technique that being used in some industrial applications. This paper presents such an immunity-based algorithm for tool breakage detection. The method is inspired by the negative-selection mechanism of the immune system, which is able to discriminate between the self (body elements) and the non-self (foreign pathogens). Howeve...

A VLSI circuit test scheme taking inspiration from the Human Immune System is presented. Such a scheme is based on the Negative-Selection Mechanism which provides the human body with the capability to discriminate between the self (body’s own cell) and any foreign cell (non-self). Based on this, it is design a output response analyzer which is able to evaluate is the circuit is faulty. Experime...

This review paper attempts to position the area of Artificial Immune Systems (AIS) in a broader context of interdisciplinary research. We review AIS based on an established conceptual framework that encapsulates mathematical and computational modelling of immunology, abstraction and then development of engineered systems. We argue that Artificial Immune Systems are much more than engineered sys...

An artificial immune system (ARTIS) is described which incorporates many properties of natural immune systems, including diversity, distributed computation, error tolerance, dynamic learning and adaptation, and self-monitoring. ARTIS is a general framework for a distributed adaptive system and could, in principle, be applied to many domains. In this paper, ARTIS is applied to computer security ...

Bio-inspired computing has lately demonstrated its usefulness with remarkable contributions to shape detection, optimization, and classification in pattern recognition. Similarly, multithreshold selection has become a critical step for image analysis and computer vision sparking considerable efforts to design an optimal multi-threshold estimator. This paper presents an algorithm for multi-thres...

AIRS, a resource limited artificial immune classifier system, has performed well on various classification tasks, including data clustering. This thesis proposes the use of this system for the complex task of multi-class document classification. Initially the AIRS system is validated using a standard machine learning dataset, which has not been used previously with this classifier. The use of A...

In the paper, an improved clone selection algorithm for cryptography optimization is proposed, the algorithm integrates genetic algorithm with immune computing and makes use of reproduction and mutation operator to maintain the diversity and optimization of candidate objects. As an experiment of the clone algorithm, a blind signcryption scheme with immune optimized parameter is proposed. In the...