In this paper a novel method for detection of network attacks and malicious code is described. The method is based on main principles of Artificial Immune Systems where immune detectors have an Artificial Neural Network’s structure. The main goal of proposed approach is to detect unknown, previous unseen cyber attacks (malicious code, intrusion detection, etc.). The mechanism of evolution of th...

Previous research has shown that artificial immune systems can be used to produce robust schedules in a manufacturing environment. The main goal is to develop building blocks (antibodies) of partial schedules that can be used to construct backup solutions (antigens) when disturbances occur during production. The building blocks are created based upon underpinning ideas from artificial immune sy...

The automatic diagnosis of breast cancer is an important, real-world medical problem. In this paper we give an introduction to fuzzy systems, genetic algorithms and artificial immune system, and then we introduce a hybrid algorithm that gathers the genetic algorithms with the artificial immune system in one algorithm. The genetic algorithm, the artificial immune system and the hybrid algorithm ...

As mobile devices become increasingly more powerful and important in everyday life, the need for efficient and effective detection of mobile malware has become pressing. We developed a multi-detector set Artificial Immune System (mAIS) to classify apps into benign and malicious categories based upon information flows within the app. The performance of mAIS has been compared with the performance...

Artificial Immune Systems have been used successfully to build recommender systems for film databases. In this research, an attempt is made to extend this idea to web site recommendation. A collection of more than 1000 individuals’ web profiles (alternatively called preferences / favourites / bookmarks file) will be used. URLs will be classified using the DMOZ (Directory Mozilla) database of th...

The word wide sharply increase in the number of smartphones user, the Android platform pose to becoming a market fugleman that makes the need for malware analysis on this platform an urgent issue. The current Artificial Immune Based malware detection systems they focus on traditional computers that uses information from OS or network, but the smartphone software behavior has its own structure a...

Living organisms demonstrate through millions of years evolution remarkably fault-tolerance, robustness and self-healing abilities. Taking inspiration from biological immune systems and embryonic processes which acquire some of these fault-tolerant properties, the paper presents the implementation of an embryonic machine with FPGA-based multi cellular architecture, which is able to imitate cell...

Artificial Immune Systems (AIS), inspired by the human immune system, are algorithms and mechanisms which are self-adaptive and self-learning classifiers capable of recognizing and classifying by learning, long-term memory and association. Unlike other human system inspired techniques like genetic algorithms and neural networks, AIS includes a range of algorithms modeling on different immune me...

We introduce several enhancements to deal with some of the weaknesses of previous artificial immune system models. Then, we present a framework for the accomplishment of several classical data mining tasks, such as frequent itemset discovery and robust clustering, based on ideas inspired from the natural immune system coupled with soft computing. For instance, we implement an artificial immune ...

In the last few years, researchers have shown great interest in studying biologically inspired systems in the domain of computer science, sociology, economics and so on. Among these, computer science has made significant advances with biologically inspired theories fitted in every branch. The typical bio-inspired systems are artificial neural networks, evolutionary computation, DNA computation,...