Fakulta elektrotechniky a informatiky / Faculty of Electrical Engineering and Informatics
Stálý URI pro tuto komunituhttps://hdl.handle.net/10195/3847
Práce obhájené před rokem 2008 jsou uloženy pouze v kolekci Vysokoškolské kvalifikační práce
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Článekpeer-reviewedpublished version Otevřený přístup Optimization of a Depiction Procedure for an Artificial Intelligence-Based Network Protection System Using a Genetic Algorithm(MDPI, 2021) Doležel, Petr; Holík, Filip; Merta, Jan; Štursa, DominikThe current demand for remote work, remote teaching and video conferencing has brought a surge not only in network traffic, but unfortunately, in the number of attacks as well. Having reliable, safe and secure functionality of various network services has never been more important. Another serious phenomenon that is apparent these days and that must not be discounted is the growing use of artificial intelligence techniques for carrying out network attacks. To combat these attacks, effective protection methods must also utilize artificial intelligence. Hence, we are introducing a specific neural network-based decision procedure that can be considered for application in any flow characteristic-based network-traffic-handling controller. This decision procedure is based on a convolutional neural network that processes the incoming flow characteristics and provides a decision; the procedure can be understood as a firewall rule. The main advantage of this decision procedure is its depiction process, which has the ability to transform the incoming flow characteristics into a graphical structure. Graphical structures are regarded as very efficient data structures for processing by convolutional neural networks. This article's main contribution consists of the development and improvement of the depiction process using a genetic algorithm. The results presented at the end of the article show that the decision procedure using an optimized depiction process brings significant improvements in comparison to previous experiments.Konferenční objektpeer-reviewedpostprint Otevřený přístup Diagnostics support of musculoskeletal diseases using artificial neural network(IEEE (Institute of Electrical and Electronics Engineers), 2021) Novotný, Zdeněk; Mareš, Jan; Doležel, PetrA vestibular schwannoma is a benign tumor, developing in the inner ear. As it grows, it may affect patient's hearing and body balance. If not treated, it can also lead to death of the patient. Once it becomes a problem, it is surgically removed. During the surgery, there is a high risk that surrounding nerves become harmed (it causes problems with facial movement). This document discusses evaluation of such injury, based on a modern approach of classification using artificial neural network.Konferenční objektpeer-reviewedpostprint Otevřený přístup Development of Artificial Intelligence Based Module to Industrial Network Protection System(Springer Nature Switzerland AG, 2020) Holík, Filip; Doležel, Petr; Merta, Jan; Štursa, DominikThe paper deals with the software-defined networking concept applied to industrial networks. This innovative concept supports network programmability and dynamic implementation of customized features, including security related ones. In a previous work of the authors, the industrial network protection system (INPS) was designed and implemented. The INPS provides complex security features of various traditional and modern security solutions within a single system. In this paper, the AI module, which is one of the crucial parts of the INPS, is dealt with. In particular, a detailed report focused on the development of the AI module decision function is provided. As a result, an artificial neural network, used for the network traffic evaluation in the AI module, is developed and comprehensively tested.