Now showing 1 - 8 of 8
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Security Aspects of Information Structures in the Information Warfare Context

2018, Grabusts, Pēteris

In the modern sense, the concept of information warfare includes the use and management of information and communication technologies to achieve a competitive advantage compared to the opponent. An information warfare is a manipulation with information that trusts a goal without an objective understanding, so that the goal is to take decisions against its own interests in the interests of the opponents. Information structures are considered as systems that produce and process various types of information, provide the storage of information and access to users. Such information structures may include neural networks, adaptive learning systems, etc. They must be prepared to train, respond to threats and ensure the safety of their existence, which is very topical during modern information warfare. This analytical article will cover more theoretical aspects related to the security of information systems from the system theory point of view. Knowledge base of the information structure can be a neural network, in which training should be provided from external threats.The author considers artificial neural networks as one of the potential threats in the context of information warfare.

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DATA MINING TEACHING POSSIBILITIES USING MATLAB

2018, Grabusts, Pēteris, Zorins, Aleksejs

The teaching experience in the study process shows that students are better at perceiving graphical information rather than analytical relationships. Many training courses run on models that were previously available only in mathematics or physics. The use of Matlab package for the implementation of various algorithms in the Information Technology fields could be a possible solution. Often, the analytical solution is much simpler than the visual Matlab model, but for the purposes of perspective training it gives understanding of the usefulness of using such models. In the previous articles the authors had given examples of how Matlab's possibilities could be used for economic research purposes (optimal tax rate searching and modelling market equilibrium price). Students are very interested in modern data mining methods, such as artificial neural networks. In the research part of the study, the modelling capabilities in data mining studies are demonstrated by neural network examples.

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Ensuring the security of information structures in today's environment

2018, Grabusts, Pēteris

In the modern sense, the concept of information warfare includes the use and management of information and communication technologies to achieve a competitive advantage compared to the opponent. An information warfare is a manipulation with information that trusts a goal without an objective understanding, so that the goal is to take decisions against its own interests in the interests of the opponents. Information structures are considered as systems that produce and process various types of information, provide the storage of information and access to users. Such information structures may include neural networks, adaptive learning systems, etc. This analytical article will cover more theoretical aspects related to the security of information systems from the system theory point of view. The author considers artificial neural networks as one of the potential threats in the context of information warfare.

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Rule based design using clustering for knowledge acquisition

2020-07-20, Grabusts, Pēteris

Data analysis can be done by expert system decisions on system status according to system input and output data. For the purpose of data analysis, there is often a need to classify data or to find regularities therein. The results of the regularity search can be expressed by the IF-THEN production rules. The use of different approaches – with clustering algorithms, neural networks – makes it possible to obtain rules that characterise data. Knowledge acquisition in this paper is the process of extracting knowledge from numerical data in form of rules. Rules acquisition in this context is based on clustering methods. With the help of the K-means clustering algorithm, rules are derived from trained neural networks. The rule-making methodology is demonstrated on a sample basis of IRIS data. The effectiveness of the obtained rules is evaluated.

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EXTRACTING RULES FROM TRAINED RBF NEURAL NETWORKS

2005, Grabusts, Pēteris

This paper describes a method of rule extraction from trained artificial neural networks. The statement of the problem is given. The aim of rule extraction procedure and suitable neural networks for rule extraction are outlined. The RULEX rule extraction algorithm is discussed that is based on the radial basis function (RBF) neural network. The extracted rules can help discover and analyze the rule set hidden in data sets. The paper contains an implementation example, which is shown through standalone IRIS data set.

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INFORMATIONAL WARFARE – INFLUENCE ON INFORMATIONAL STRUCTURES

2019, Grabusts, Pēteris, Zorins, Aleksejs, Teilāns, Artis

The concept of information warfare encompasses the use of information and communication technologies to gain an advantage over a potential opponent. The information warfare is the manipulation with the information that trusts the goal, so that the goal should make decisions about its interests in the interests of opponents. Information structures are treated as systems that process different types of information, provide storage and access to users. Such structures may enclose neural networks, self-learning systems etc. They need to be ready to learn, respond to threats and ensure their safety, which is topical in today's information warfare. This paper will address aspects related to the security of information systems from a system theory point of view. The knowledge base of information structures can be elements of artificial intelligence, which security must be protected against various threats. The authors considers artificial neural networks to be one of the potential threats in the context of information warfare.

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The Influence of Hidden Neurons Factor on Neural Nework Training Quality Assurance

2015, Grabusts, Pēteris, Zorins, Aleksejs

The work shows the role of hidden neurons in the multilayer feed-forward neural networks. The numeric expression of hidden neurons is usually determined in each case empirically. The methodology for determining the number of hidden neurons are described. The neural network based approach is analyzed using a multilayer feed-forward network with backpropagation learning algorithm. We have presented neural network implementation possibility in bankruptcy prediction (the experiments have been performed in the Matlab environment). On the base of bankruptcy data analysis the effect of hidden neurons to specific neural network training quality is shown. The conformity of theoretical hidden neurons to practical solutions was carried out.

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Security Protocols Analysis in Relation to Information Structures Protection

2019, Grabusts, Pēteris

The concept of information warfare encompasses the use of information and communication technologies to gain an advantage over a potential opponent. The information warfare is the manipulation with the information that trusts the goal, so that the goal should make decisions about its interests in the interests of opponents. Information structures are treated as systems that process different types of information, provide storage and access to users. Such structures may enclose neural networks, self-learning systems etc. They need to be ready to learn, respond to threats and ensure their safety, which is topical in today's information warfare. The paper will examine theoretical aspects of ensuring the security of information structures from the system theory point of view. The description of information structures, analysis of their security protocols will be given. The knowledge base of the information structure can be a neural network, the training of which is secured from external interference. The research presents a description of a potential counteraction against the threats of information warfare against information systems (AI based on artificial neural networks). The CORAS methodology for risk analysis in case of threats to information structures was discussed.