BUDOWA SYSTEMÓW WYKRYWANIA ATAKÓW NA PODSTAWIE METOD INTELIGENTNEJ ANALIZY DANYCH

Nowadays, with the rapid development of network technologies and with global informatization of society problems come to the fore ensuring a high level of information system security. With the increase in the number of computer security incidents, intrusion detection systems (IDS) started to be developed rapidly.Nowadays the intrusion detection systems usually represent software or hardware-software solutions, that automate the event control process, occurring in an information system or network, as well as independently analyze these events in search of signs of security problems. A modern approach to building intrusion detection systems is full of flaws and vulnerabilities, which allows, unfortunately, harmful influences successfully overcome information security systems. The application of methods for analyzing data makes it possible identification of previously unknown, non-trivial, practically useful and accessible interpretations of knowledge necessary for making decisions in various spheres of human activity. The combination of these methods along with an integrated decision support system makes it possible to build an effective system for detecting and counteracting attacks, which is confirmed by the results of imitation modeling.W chwili obecnej szybki rozwój technologii sieciowych i globalnej informatyzacji społeczeństwa uwypukla problemy związane z zapewnieniem wysokiego poziomu bezpieczeństwa systemów informacyjnych. Wraz ze wzrostem liczby incydentów komputerowych związanych z bezpieczeństwem nastąpił dynamiczny rozwój systemów wykrywania ataków. Obecnie systemy wykrywania włamań i ataków to zazwyczaj oprogramowanie lub sprzętowo-programowe rozwiązania automatyzujące proces monitorowania zdarzeń występujących w systemie informatycznym lub sieci, a także samodzielnie analizujące te zdarzenia w poszukiwaniu oznak problemów bezpieczeństwa. Nowoczesne podejście do budowy systemów wykrywania ataków na systemy informacyjne jest pełne wad i słabych punktów, które niestety pozwalają szkodliwym wpływom na skuteczne pokonanie systemów zabezpieczania informacji. Zastosowanie metod inteligentnej analizy danych pozwala wykryć w danych nieznane wcześniej, nietrywialne, praktycznie użyteczne i dostępne interpretacje wiedzy niezbędnej do podejmowania decyzji w różnych sferach ludzkiej działalności. Połączenie tych metod wraz ze zintegrowanym systemem wspomagania decyzji umożliwia zbudowanie skutecznego systemu wykrywania i przeciwdziałania atakom, co potwierdzają wyniki modelowania

Comparative Analysis of Data Security and Cloud Storage Models Using NSL KDD Dataset

Cloud computing is becoming increasingly important in many enterprises, and researchers are focusing on safeguarding cloud computing. Due to the extensive variety of service options it offers, A significant amount of interest from the scientific community has been focused on cloud computing. The two biggest problems with cloud computing are security and privacy. The key challenge is maintaining privacy, which expands rapidly with the number of users. A perfect security system must efficiently ensure each security aspect. This study provides a literature review illustrating the security in the cloud with respect to privacy, integrity, confidentiality and availability, and it also provides a comparison table illustrating the differences between various security and storage models with respect to the approaches and components of the models offered. This study also compares Naïve Bayes and SVM on the accuracy, recall and precision metrics using the NSL KDD dataset

Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

Parameters and Structure of Neural Network Databases for Assessment of Learning Outcomes

The purpose of this study is to determine the methodology, develop a theory of construction, put into practice algorithmization and implement the functionality of a hybrid intelligent system for assessment of educational outcomes of trainees on the basis of the identified keyword parameters and structure of the artificial neural network using expert systems and fuzzy simulation; to develop a methodology for the construction of structural-logic, hierarchical, functional and fractal schemes for structuring databases of the didactic field of learning elements; to determine the content, structure of parameters and database components, selection criteria and the content of complexes of educational standards. The methodology of introducing intelligent systems into mathematical education is on the basis of the Hegelian triad: thesis (implementation of the coherence principle) – antithesis (implementation of principles of the fractality and historiogenesis) – synthesis (implementation of the principles of self-organization and reflection of the complex system inversion integrity). Requirements for the organization and construction of the artificial neural network for assessment of personal achievements on the basis of fuzzy simulation have been developed. In the direction of using elements of fractal geometry, the technological structures of clusters that constitute the basis of generalized structures have been developed. In particular, it is revealed that the didactic field of learning elements is equipped with a system of multi-level hierarchical databases of exercises, motivational-applied, research, practice-oriented tasks using expert systems and integration of mathematical, information, natural-science and humanities knowledge and procedures

Measurements, Models, Systems and Design

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Acesso remoto dinâmico e seguro a bases de dados com integração de políticas de acesso suave

The amount of data being created and shared has grown greatly in recent years, thanks in part to social media and the growth of smart devices. Managing the storage and processing of this data can give a competitive edge when used to create new services, to enhance targeted advertising, etc. To achieve this, the data must be accessed and processed. When applications that access this data are developed, tools such as Java Database Connectivity, ADO.NET and Hibernate are typically used. However, while these tools aim to bridge the gap between databases and the object-oriented programming paradigm, they focus only on the connectivity issue. This leads to increased development time as developers need to master the access policies to write correct queries. Moreover, when used in database applications within noncontrolled environments, other issues emerge such as database credentials theft; application authentication; authorization and auditing of large groups of new users seeking access to data, potentially with vague requirements; network eavesdropping for data and credential disclosure; impersonating database servers for data modification; application tampering for unrestricted database access and data disclosure; etc. Therefore, an architecture capable of addressing these issues is necessary to build a reliable set of access control solutions to expand and simplify the application scenarios of access control systems. The objective, then, is to secure the remote access to databases, since database applications may be used in hard-to-control environments and physical access to the host machines/network may not be always protected. Furthermore, the authorization process should dynamically grant the appropriate permissions to users that have not been explicitly authorized to handle large groups seeking access to data. This includes scenarios where the definition of the access requirements is difficult due to their vagueness, usually requiring a security expert to authorize each user individually. This is achieved by integrating and auditing soft access policies based on fuzzy set theory in the access control decision-making process. A proof-of-concept of this architecture is provided alongside a functional and performance assessment.A quantidade de dados criados e partilhados tem crescido nos últimos anos, em parte graças às redes sociais e à proliferação dos dispositivos inteligentes. A gestão do armazenamento e processamento destes dados pode fornecer uma vantagem competitiva quando usados para criar novos serviços, para melhorar a publicidade direcionada, etc. Para atingir este objetivo, os dados devem ser acedidos e processados. Quando as aplicações que acedem a estes dados são desenvolvidos, ferramentas como Java Database Connectivity, ADO.NET e Hibernate são normalmente utilizados. No entanto, embora estas ferramentas tenham como objetivo preencher a lacuna entre as bases de dados e o paradigma da programação orientada por objetos, elas concentram-se apenas na questão da conectividade. Isto aumenta o tempo de desenvolvimento, pois os programadores precisam dominar as políticas de acesso para escrever consultas corretas. Além disso, quando usado em aplicações de bases de dados em ambientes não controlados, surgem outros problemas, como roubo de credenciais da base de dados; autenticação de aplicações; autorização e auditoria de grandes grupos de novos utilizadores que procuram acesso aos dados, potencialmente com requisitos vagos; escuta da rede para obtenção de dados e credenciais; personificação de servidores de bases de dados para modificação de dados; manipulação de aplicações para acesso ilimitado à base de dados e divulgação de dados; etc. Uma arquitetura capaz de resolver esses problemas é necessária para construir um conjunto confiável de soluções de controlo de acesso, para expandir e simplificar os cenários de aplicação destes sistemas. O objetivo, então, é proteger o acesso remoto a bases de dados, uma vez que as aplicações de bases de dados podem ser usados em ambientes de difícil controlo e o acesso físico às máquinas/rede nem sempre está protegido. Adicionalmente, o processo de autorização deve conceder dinamicamente as permissões adequadas aos utilizadores que não foram explicitamente autorizados para suportar grupos grandes de utilizadores que procuram aceder aos dados. Isto inclui cenários em que a definição dos requisitos de acesso é difícil devido à sua imprecisão, geralmente exigindo um especialista em segurança para autorizar cada utilizador individualmente. Este objetivo é atingido no processo de decisão de controlo de acesso com a integração e auditaria das políticas de acesso suaves baseadas na teoria de conjuntos difusos. Uma prova de conceito desta arquitetura é fornecida em conjunto com uma avaliação funcional e de desempenho.Programa Doutoral em Informátic

Future Trends and Directions for Secure Infrastructure Architecture in the Education Sector: A Systematic Review of Recent Evidence

The most efficient approach to giving large numbers of students’ access to computational resources is through a data center. A contemporary method for building the data center\u27s computer infrastructure is the software-defined model, which enables user tasks to be processed in a reasonable amount of time and at a reasonable cost. The researcher examines potential directions and trends for a secured infrastructure design in this article. Additionally, interoperable, highly reusable modules that can include the newest trends in the education industry are made possible by cloud-based educational software. The Reference Architecture for University Education System Using AWS Services is presented in the paper. In conclusion, automation boosts efficiency by 20% while decreasing researcher involvement in kinetics modeling using CHEMKIN by 10%. Future work will focus on integrating GPUs into open-source programs that will be automated and shared on CloudFlame as a service resource for cooperation in the educational sector

AI-Augmented HRM: Literature review and a proposed multilevel framework for future research.

The research using artificial intelligence (AI) applications in HRM functional areas has gained much traction and a steep surge over the last three years. The extant literature observes that contemporary AI applications have augmented HR functionalities. AI-Augmented HRM HRM(AI) has assumed strategic importance for achieving HRM domain-level outcomes and organisational outcomes for a sustainable competitive advantage. Moreover, there is increasing evidence of literature reviews pertaining to the use of AI applications in different management disciplines (i.e., marketing, supply chain, accounting, hospitality, and education). There is a considerable gap in existing studies regarding a focused, systematic literature review on HRM(AI), specifically for a multilevel framework that can offer research scholars a platform to conduct potential future research. To address this gap, the authors present a systematic literature review (SLR) of 56 articles published in 35 peer-reviewed academic journals from October 1990 to December 2021. The purpose is to analyse the context (i.e., chronological distribution, geographic spread, sector-wise distribution, theories, and methods used) and the theoretical content (key themes) of HRM(AI) research and identify gaps to present a robust multilevel framework for future research. Based upon this SLR, the authors identify noticeable research gaps, mainly stemming from - unequal distribution of previous HRM(AI) research in terms of the smaller number of sector/country-specific studies, absence of sound theoretical base/frameworks, more research on routine HR functions(i.e. recruitment and selection) and significantly less empirical research. We also found minimal research evidence that links HRM(AI) and organisational-level outcomes. To overcome this gap, we propose a multilevel framework that offers a platform for future researchers to draw linkage among diverse variables starting from the contextual level to HRM and organisational level outcomes that eventually enhance operational and financial organisational performance

Artificial Intelligence-based Control Techniques for HVDC Systems

The electrical energy industry depends, among other things, on the ability of networks to deal with uncertainties from several directions. Smart-grid systems in high-voltage direct current (HVDC) networks, being an application of artificial intelligence (AI), are a reliable way to achieve this goal as they solve complex problems in power system engineering using AI algorithms. Due to their distinctive characteristics, they are usually effective approaches for optimization problems. They have been successfully applied to HVDC systems. This paper presents a number of issues in HVDC transmission systems. It reviews AI applications such as HVDC transmission system controllers and power flow control within DC grids in multi-terminal HVDC systems. Advancements in HVDC systems enable better performance under varying conditions to obtain the optimal dynamic response in practical settings. However, they also pose difficulties in mathematical modeling as they are non-linear and complex. ANN-based controllers have replaced traditional PI controllers in the rectifier of the HVDC link. Moreover, the combination of ANN and fuzzy logic has proven to be a powerful strategy for controlling excessively non-linear loads. Future research can focus on developing AI algorithms for an advanced control scheme for UPFC devices. Also, there is a need for a comprehensive analysis of power fluctuations or steady-state errors that can be eliminated by the quick response of this control scheme. This survey was informed by the need to develop adaptive AI controllers to enhance the performance of HVDC systems based on their promising results in the control of power systems. Doi: 10.28991/ESJ-2023-07-02-024 Full Text: PD