Immune neural network

Intrusion detection systems (IDS) are used as a computer network security tool and permit to alert an administrator in case of attack. The main goal of IDS is to detect and recognize network attacks in real time. Nowadays there exist different approaches for intrusion detection. It is signature analysis, rule-based method, embedded sensors, neural networks, artificial immune systems [1]—[6] and so on. The most of these IDS can detect the known attacks and have poor ability to detect new attacks. 

Josephson arrays Heart cell synchronization Neural networks Immune system Ecosystems... 

Keywords Intrusion Detection System (IDS) Feature selection, Immunity Algorithm (IA), Back Propagation Neural Network (BPNN)... 

Research on method of automatic recognition of coal mine water inrush sources based on Immune Algorithm and Back Propagation Neural Network... 

In this paper, a plurality of data of analysis of ground water quality test were pre-processed with Immune Algorithm (lA). The key characteristics of coal mine water inrush source data are extracted by characteristic analysis method. The complexity of the data is reduced by reducing the dimensionality of the data set. With the help of the data after dimension reduction, the Back Propagation Neural Network (BPNN) is trained. The coal mine water inrush source is recognized by the trained BPNN. Experiments show that if the source of mine disaster water is identified by the method developed in the paper, its accuracy can reach 93%. The more detailed introduction on the method is given below. 

Abstract. In this paper we present an Abstract Immune System Algorithm, based on the model introduced by Farmer et at, inspired on the theory of Clonal Selection and Idiotypic Network due to Niels Jeme. The proposed algorithm can be used in order to solve problems much in the way that Evolutionary Algorithms or Artificial Neural Networks do. Besides presenting the Algorithm itself, we briefly discuss its various parameters, how to encode input data and how to extract the output data from its outcome. The reader can do their own experiments using the workbench found in the address http //ctp.di.fct.unl.pt/ jddp/immune/. 

The AI Methods From Neural Networks to Immune Systems... 

In the same way as the artificial neural network is not a model of the human brain so an artificial immune system is not a model of the human immune system. Once again we are dealing with biological inspiration, i.e. an attempt to build a system that mimics the features and uses rules of the immune system. 

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