This paper proposes a hybrid optimization method based on the fusion of the Simulated Annealing (SA) and Clonal Selection Algorithm (CSA), in which the SA is embedded in the CSA to enhance its search capability. The novel optimization algorithm is also employed to deal with several nonlinear benchmark functions as well as a practical engineering design problem. Simulation results demonstrate th...

Artificial immune systems (AIS) use the concepts and algorithms inspired by the theory of how the human immune system works. This document presents the design and initial evaluation of a new artificial immune system for collaborative spam filtering. Collaborative spam filtering allows for the detection of not-previously-seen spam content, by exploiting its bulkiness. Our system uses two novel a...

The adaptable lymphocyte hypothesis is identified as a possible source of inspiration for artificial immune systems. Based on a number of qualitative investigations we identify some properties of a theoretical system (the tunable activation threshold model and excitability) that could be applicable in an engineering domain. An example is shown of how we could exploit these properties.

One of the central challenges with computer security is determining the difference between normal and potentially harmful activity. For decades, developers have protected their systems using classical methods. However, the growth and complexity of computer systems or networks to protect require the development of automated and adaptive defensives tools. Promising solutions are emerging with bio...

Bloom filter is a probabilistic and space efficient data structure designed to check the membership of an element in a set. The trade-off to use Bloom filter may have configurable risk of false positives. The percentages of a false positive can be made low if the hash bit map is sufficiently massive. Spam is an unsolicited or irrelevant message sent on the internet to an outsized range of users...

The paper concentrates on analyzing associative properties of Artificial Immune Systems, especially on immunological memory, which is a member of a class of sparse and distributed associative memories [18]. This class of memories derives its associative and robust nature by sparsely sampling the input space and distributing the data among many independent agents [16]. Immunological memory is on...

The field of Artificial Immune Systems (AIS) concerns the study and development of computationally interesting abstractions of the immune system. This survey tracks the development of AIS since its inception, and then attempts to make an assessment of its usefulness, defined in terms of 'distinctiveness' and 'effectiveness.' In this paper, the standard types of AIS are examined--Negative Select...

1 Polytechnic of Bari, Via E. Orabona 4, 70125 Bari, Italy [email protected] 2 National Cancer Institute ‘Giovanni Paolo II’, Via F. Hahnemann 10, 70126 Bari, Italy [email protected] 3 Federal Technological University of Paraná, Av. 7 de setembro, 3165 Curitba, Brazil [email protected] 4 University of Catania, Viale A. Doria 6, 95125 Catania, Italy [email protected] 5 Computing L...

In this paper, we focus on the potential for applying Kernel Methods into Artificial Immune Systems. This is based on the fact that the commonly employed “affinity functions” can usually be replaced by kernel functions, leading to algorithms operating in the feature space. A discussion of this applicability in negative/positive selection algorithms, the dendritic cell algorithm and immune netwo...

The objective of the proposed work is to formally verify and implement an Artificial Immune Networking model. The work focuses on the protection against computer viruses which disrupt the normal usage of the network. The vulnerability of the network due to the malfunctions is detected in terms of faulty or malicious nodes. An Artificial Immune System or Bio-Inspired approach is adopted by makin...