The article describes the investigation process of the possibilities of XSS–attacks, and the development of counteraction means to these attacks. Researches were determined whether XSS–attack can be fulfilled successfully, and vulnerability detection methods can be applied; were developed the logical and structural diagrams of XSS–vulnerability detection program; were realized program implementation (software) of algorithms for detecting XSS–vulnerabilities on the Web – sites. The software implementation is Web extension for the Google Chrome browser. Main purpose of implementing this software is to confirm or deny the presence of XSS–vulnerabilities on the site, and to counteract the possible attack.
This article is devoted to the issue of regulating traffic congestion in major cities of the world using artificial neural networks. Research is aimed at developing import – substituting automated intelligent system that uses artificial neural network to make decisions to optimize traffic congestion by changing the duration of light phases of traffic lights. Multilayer perceptron with sigmoidal activation function is used as neural network. The article describes developing stages of intelligent automated traffic control system that using artificial neural networks allows making informed decisions based on extensive analysis of available information, as well as constantly adapt it to incoming external influences that lead to non – equilibrium state. Practical application of the proposed system is expressed in unloading road sections adjacent to highway; reducing the number of traffic jams in the lanes or reducing the length of the car queue; automating traffic control and reducing the number of emergency cases that require inspection personnel to leave for manual control. System allow improving overall traffic situation by avoiding cascading traffic jams on adjacent sections; prevention of accidents and conflicts between motorists and pedestrians; improving the reliability of adjustment and reducing cost of maintenance infrastructure.
Problem of safety ensuring of children and underage adolescents in Web–space is becoming increasingly acute. Younger generation information security is the state of children and adolescents protection, in which there is no risk associated with harm to their health and (or) physical, mental, spiritual, moral development from destructive information. This article describes the development of new software product that allows analyzing text from files, Web sites, pages, applications, etc. Analog programs were reviewed; modern text recognition algorithms were described. Screenshots and flowchart of software parts designed functioning for semantic text analysis in Web space are presented. Any Web page is file with extension, and after analyzing, it is possible to evaluate the information and classify it by topics, as well as to determine whether there is destructive content. In the presented study, the software tool was developed for semantic analysis and formalization of text. Exact trigger points from 26 to 30 times evaluate the algorithm functioning. With accuracy of up to 80%, it can be argued that algorithm is suitable for determining the orientation of article and content of ideas expressed in it, taking into account duality of model.
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