Malicious software (malware) infects large numbers of mobile devices. Once infected these mobile devices may be involved in many kinds of online criminal activity, including identity theft, unsolicited commercial SMS messages, scams and massive coordinated attacks. Until recently, mobile networks have been relatively isolated from the Internet, so there has been little need to protect them agai...

Artificial immune systems (AIS) are often developed directly from textual descriptions of immune properties with little attempt to understand those properties free of an engineering domain or application. Here we present an example of how an AIS can be developed based on an in-depth investigation of an immune model. This model describes how the activation thresholds of immune cells can be tuned...

This paper investigates the relevance of the immune system metaphor to Time Dependent Optimization (TDO). The main feature of immune approaches is their immunization capability. In Time Dependent Optimization, this could help to memorize previously encountered optima in order to improve robustness when facing them again. This paper proposes two simple models of artificial Immune Systems and dis...

This thesis examines the role of wireless sensor networks, as illustrated by specknets, as an appropriate platform for developing novel immune-inspired algorithms. Properties of the immune system and wireless sensor networks are examined in parallel, revealing a potential mapping between the two. The cognitive view of the immune system is identified as appropriate for further investigation at t...

We apply the Artificial Immune System (AIS) technology to the Collaborative Filtering (CF) technology when we build the movie recommendation system. Two different affinity measure algorithms of AIS, Kendall tau and Weighted Kappa, are used to calculate the correlation coefficients for this movie recommendation system. From the testing we think that Weighted Kappa is more suitable than Kendall t...

González, Fabio Ph.D. The University of Memphis. May 2003. A Study of Artificial Immune Systems Applied to Anomaly Detection. Major Professor: Dipankar Dasgupta, Ph.D. The main goal of this research is to examine and to improve the anomaly detection function of artificial immune systems, specifically the negative selection algorithm and other self/non-self recognition techniques. This research ...

Artificial immune systems (AIS) can be defined as computational systems inspired by theoretical immunology, observed immune functions, principles and mechanisms in order to solve problems. Their development and application domains follow those of soft computing paradigms such as artificial neural networks (ANN), evolutionary algorithms (EA) and fuzzy systems (FS). Despite some isolated efforts,...

In recent decades, Artificial Immune Systems (AISs) have appeared as an approach dealing with security systems and classification problems. This paper briefly surveys AIS basic concepts, features and principles, approaches and applications.

Evolutionary Intelligence is the place to discover advances in the field of evolutionary intelligence. The journal is devoted to the timely publication and dissemination of both the theoretical and practical aspects of population-based searches for artificial intelligence. Among the techniques covered are rule-based systems, artificial neural networks, fuzzy systems, Bayesian and statistical a...

Fuzzy systems were designed to compute with uncertainties and linguistic information and allow us to develop mathematical tools for information processing. Artificial immune systems (AIS) consist of methods inspired by the biological immune system and designed for solving real-world problems. This work integrates these two kinds of systems, proposing a novel AIS for discovering fuzzy classifica...