Development of Sectoral Intellectualized Expert Systems and Decision Making Support Systems in Cybersecurity

Akhmetov, Bakhytzhan; Lakhno, Valeriy; Алимсеитова, Жулдыз

doi:10.1007/978-3-030-00184-1_15

Cited by 20 publications

(13 citation statements)

References 15 publications

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“…The ICS infrastructure from the point of view of ensuring CS and IP is presented on Figure 1. By default, standard IPT [23] are installed in the ICS nodes: antivirus; firewall; tools for: 1) intrusion detection 2) cryptographic IP; 3) access control; 4) integrity control; 5) authentication, etc. Naturally, for a specific ICS, the list can be supplemented due to insufficiency or reduced due to redundancy.…”

Section: Methods and Modelsmentioning

confidence: 99%

“…It was shown in [17] - [20] that standard and modified GAs are efficient enough to solve most complex optimization problems [23] and are promising for further study and improvement.…”

Section: Review and Analysis Of Previous Studiesmentioning

confidence: 99%

“…As a result of the DSS operation, the optimal set of IPT for ICS node is determined based on the integral indicator of each IPT from the corresponding class and cost of this IPT. As the quality index or the degree of attainability of the desired goals for a specific IPT there is accepted an integral indicator (InI) of IPT [23]. InI can also be interpreted as a generalized indicator of the quality of the most important characteristics of a particular IPT.…”

Section: G Chmentioning

confidence: 99%

“…InI can also be interpreted as a generalized indicator of the quality of the most important characteristics of a particular IPT. At the same time, we believe that the InI is calculated as the degree of proximity of the IPT parameters to ideal characteristics in the space of selected particular indicators [23]. To calculate the InI of IPT, the following dependence was used:…”

Section: G Chmentioning

confidence: 99%

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Decision Support System on Optimization of Information Protection Tools Placement

A¹

2020

IJATCSE

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The article discusses the possibilities of modifying the genetic algorithm (GA) to solve the problem of selecting and optimizing the configuration of information protection tools (IPT) for the security circuits of information and communication systems (ICS). The scientific novelty of the work lies in the fact that the GA proposes the use of the total amount of risks from information loss, as well as the integral indicator of IPT and cost indicators for each class of IPT, as criteria for optimizing the composition of IPT. The genetic algorithm in the problem of optimizing the choice of the composition of IPT for ICS is considered as a variation of the problem associated with multi-selection. In this regard, the optimization of the IPT placement along the ICS protection circuits is considered as a modification of the combinatorial knapsack problem. The GA used in the computing core of the decision support system (DSS) differs from the standard GA. As a part of the GA modification, the chromosomes are presented in the form of matrices, the elements of which are numbers that correspond to the IPT numbers in the ICS nodes. In the process of modifying the GA, a k-point crossing-over was applied. A fitness function is presented as the sum of efficiency factors. At the same time, in addition to the traditional absolute indicators of the IPT efficiency, the total value of risks from information loss, as well as cost indicators for each class of IPT are taken into account. The practical value of the research lies in the implementation of DSS based on the proposed modification of GA. Computational experiments on the selection of a rational software algorithm for implementing the model are performed. It is shown that the implementation of the GA in DSS allows to accelerate the search for optimal variants of cybersecurity (CS) tools placement for ICS by more than 25 times. This advantage allows not only to quickly search through the variety of hardware-software IPT and their combinations for ICS, but also to combine the proposed algorithm with the available models and algorithms for optimizing the composition of the ICS cybersecurity circuits. Potentially, such a combination of models and algorithms will make it possible to quickly rebuild the ICS protection, adjusting its profiles in accordance with new threats and classes of cyber attacks.

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Section: Methods and Modelsmentioning

confidence: 99%

“…It was shown in [17] - [20] that standard and modified GAs are efficient enough to solve most complex optimization problems [23] and are promising for further study and improvement.…”

Section: Review and Analysis Of Previous Studiesmentioning

confidence: 99%

Section: G Chmentioning

confidence: 99%

Section: G Chmentioning

confidence: 99%

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Decision Support System on Optimization of Information Protection Tools Placement

A¹

2020

IJATCSE

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“…Therefore, the proposed toolkit will allow the participants of the investment process in CSS of ICTS to improve significantly the performance indicators of their activities. In addition, the joint use of software products such as IDSS "SSDMI" and an adaptive expert system for the recognition of cyberthreats (described in the works of the authors [20,21,23]) will allow investors not only at the stage of initial analysis of the project, but at the modernization of existing systems of cybersecurity, in particular, for critical computer infrastructures, to build effectively a forward-looking policy in the field of financing of cyber security systems, taking into account the trend towards increasing the amount of threats for their ICS.…”

mentioning

confidence: 99%

Adaptive Model of Mutual Financial Investment Procedure Control in Cybersecurity Systems of Situational Transport Centers

Akhmetov¹,

Desiatko²,

Lakhno³

et al. 2019

SERIES OF GEOLOGY AND TECHNICAL SCIENCES

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NAS RK is pleased to announce that News of NAS RK. Series of geology and technical sciences scientific journal has been accepted for indexing in the Emerging Sources Citation Index, a new edition of Web of Science. Content in this index is under consideration by Clarivate Analytics to be accepted in the Science Citation Index Expanded, the Social Sciences Citation Index, and the Arts & Humanities Citation Index. The quality and depth of content Web of Science offers to researchers, authors, publishers, and institutions sets it apart from other research databases. The inclusion of News of NAS RK. Series of geology and technical sciences in the Emerging Sources Citation Index demonstrates our dedication to providing the most relevant and influential content of geology and engineering sciences to our community. Қазақстан Республикасы Ұлттық ғылым академиясы "ҚР ҰҒА Хабарлары. Геология жəне техникалық ғылымдар сериясы" ғылыми журналының Web of Science-тің жаңаланған нұсқасы Emerging Sources Citation Index-те индекстелуге қабылданғанын хабарлайды. Бұл индекстелу барысында Clarivate Analytics компаниясы журналды одан əрі the Science Citation Index Expanded, the Social Sciences Citation Index жəне the Arts & Humanities Citation Index-ке қабылдау мəселесін қарастыруда. Webof Science зерттеушілер, авторлар, баспашылар мен мекемелерге контент тереңдігі мен сапасын ұсынады. ҚР ҰҒА Хабарлары. Геология жəне техникалық ғылымдар сериясы Emerging Sources Citation Index-ке енуі біздің қоғамдастық үшін ең өзекті жəне беделді геология жəне техникалық ғылымдар бойынша контентке адалдығымызды білдіреді. НАН РК сообщает, что научный журнал «Известия НАН РК. Серия геологии и технических наук» был принят для индексирования в Emerging Sources Citation Index, обновленной версии Web of Science. Содержание в этом индексировании находится в стадии рассмотрения компанией Clarivate Analytics для дальнейшего принятия журнала в the Science Citation Index Expanded, the Social Sciences Citation Index и the Arts & Humanities Citation Index. Web of Science предлагает качество и глубину контента для исследователей, авторов, издателей и учреждений. Включение Известия НАН РК. Серия геологии и технических наук в Emerging Sources Citation Index демонстрирует нашу приверженность к наиболее актуальному и влиятельному контенту по геологии и техническим наукам для нашего сообщества.

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Malware Detection Using Artificial Neural Networks

Dychka

Chernyshеv

Tereikovskyi

et al. 2019

Advances in Computer Science for Engineering and Education II

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Development of Sectoral Intellectualized Expert Systems and Decision Making Support Systems in Cybersecurity

Cited by 20 publications

References 15 publications

Decision Support System on Optimization of Information Protection Tools Placement

Decision Support System on Optimization of Information Protection Tools Placement

Adaptive Model of Mutual Financial Investment Procedure Control in Cybersecurity Systems of Situational Transport Centers

Malware Detection Using Artificial Neural Networks

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