focusing on “distinctiveness” and “effectiveness” of algorithms inspired by natural immune system, a novel artificial immune network algorithm named immune feature extracting network (IFEN) is proposed to realize the function of feature data extracting in this paper. Based on comprehensive analysis of mechanism of natural immune system and current researching works of artificial immune system (...

Artificial Immune Systems (AIS) have long been used in the field of computer security and especially in Intrusion Detection systems. Intrusion detection based on AISs falls into two main categories. The first generation of AIS is inspired from adaptive immune reactions but, the second one which is called danger theory focuses on both adaptive and innate reactions to build a more biologically-re...

The assurance of security within a network is difficult due to the variations of attacks. This research conducts various experiments to implement an Artificial Immune System based Intrusion Detection System to identify intrusions using the Negative Selection Algorithm. This research explores the implementation of an Artificial Immune System opposed to the industry standard of machine learning. ...

Outlier detection is a data mining method for discovering exceptional, abnormal or suspiciously unusual samples in a data set. Outliers typically represent the data rich but information poor dilemma. Data mining methods are applied to solve this problem in broad range of application fields like credit card fraud detection, network intrusion detection, error extraction, clinical disease research...

Due to today’s advancement in technology and businesses, fraud detection has become a critical component of financial transactions. Considering vast amounts of data in large datasets, it becomes more difficult to detect fraud transactions manually. In this research, we propose a combined method using both data mining and statistical tasks, utilizing feature selection, resampling and cost-...

Today traditional intrusion detection systems are unable to detect intrusion attacks. Huge number of false alarm generated by the system results in financial loss of an organization. The unique features of artificial immune system encourage and motivate the researchers to employ this technique in variety of applications and especially in intrusion detection systems. Recently Artificial immune s...

This paper presents a resource limited artificial immune system for data analysis. The work presented here builds upon previous work on artificial immune systems for data analysis. A population control mechanism, inspired by the natural immune system, has been introduced to control population growth and allow termination of the learning algorithm. The new algorithm is presented, along with the ...

This work presents a cost-effective base station deployment model based on artificial immune systems. It uses a multiobjective algorithm based on artificial immune systems (MOAIS) as an optimiser. MO-AIS algorithms are a new class of evolutionary algorithms. The Binary-coded Multi-objective Optimisation Algorithm (BRMOA) is inspired by the clonal selection theory and the immune network theory. ...

A machine-learning algorithm based on the natural immune system metaphor has been developed, AINE (Artificial Immune Network). AINE developed from initial work on Artificial Immune Systems for data analysis, for which detailed experimentation was undertaken as to the affect of altering algorithm parameters had on the behaviour of the system. Two of the parameters, the network affinity threshold...