According to modern statistics and analytical reviews, targeted computer attacks (cyber attacks) are becoming more and more numerous. Attackers began to use non-standard schemes for implementing attacks, using employees of organizations as intermediaries, which reduces the efficiency of detecting violations. At the same time, the targets of attackers are increasingly critical information infrastructure (CII) objects. The number of cyberattacks on the critical infrastructure of the Russian Federation increased by 150%. Successful attacks on CII are associated with a lack of software updates for industrial equipment, personnel errors, incorrect configuration of protection tools and can potentially lead to disasters. Prediction of computer attacks on CII based on a comprehensive analysis of the characteristics of incidents and system users can significantly increase the efficiency of incident detection, since it is obvious that technical and anthropogenic characteristics in this case should be taken into account together. It is difficult to classify computer incidents due to the volume and heterogeneity of the data about them. The paper proposes approaches that provide for the initial systematization of system log data and user characteristics, an assessment of their informativeness. This will reduce the complexity of further data processing and increase the performance of the computer attack forecasting system by excluding some uninformative data from a single secure storage. The second important task is to create test systems based on available platforms for analyzing and detecting computer incidents in order to train future information security specialists in big data analysis technologies.
The article considers the specifics of automated control systems for technological production and processes as objects of information security, proposed the approach to the decomposition of their components for further evaluation of the necessary degree of protection of the data they process. The method for obtaining the quantitative assessment of the grade of information resources security is presented. The proposed method allows taking into account the data value and the degree of criticality of violations of its integrity, accessibility and confidentiality for the functioning of the system. It can be used in practice at enterprises of various kinds of activity as an independent procedure, or as part of measures at the stages of preliminary analysis of automation systems before design or improving their data protection subsystems.
The paper proposes the approach to develop a data protection system (information security system) that is optimal in effectiveness using evolutionary search methods. This approach is characterized by the ability to take into account the influence of random factors (staff qualifications, equipment failures, attack time on the protection system) when choosing a protection option and the possibility of adapting the protection system to changing environmental conditions. The development of an effective information security system using a genetic algorithm is possible on the basis of data on monitoring events in the system, data received from experts and during simulation modeling of the protection system. The research results are of applied nature and can be used in developments related to the design of information systems, decision support systems in the field of information security.
The abstract: the paper presents the urgency of the problem of integrating of medical information systems and external specialized software products.
The main goal of the paper is to optimize the process of remote monitoring of the patient’s health with an implanted device. As a result, the integration
module of the hospital information system of the Federal state budget foundation “Federal center of cardiovascular surgery” of the Ministry of Health
of the Russian Federation (Astrakhan) was introduced, in terms of the patient’s Electronic Health Records (EHR) and Medtronic CareLink remote monitoring
system. The ability to integrate various medical systems makes it possible to optimize the processing of electronic medical documents, in particular, routine
data collection and processing operations in the patient’s electronic medical record (Electronic Health Records, EHR) in the daily work of a medical specialist.
Modern society is characterized by increased progress in science and technology, accompanied by rapid uncontrolled growth and a variety of textual information, including of destructive orientation, in the information space of the Internet. In this regard, as well as in the context of the potential creation of a “closed” Internet space in the Russian Federation, solving the problem of analyzing text content by searching and automatically identifying destructive information is a priority trend. Within the framework of the paper task of identifying destructive information is reduced to the task of classifying the analyzed textual data based on the presence or absence of destructive indicators. The article describes the universal three-stage combined method, including blocks for normalizing input data, the modified dictionary search of destructive indicators and the Bayesian classifier, which allows staged search of various indicators in the text and automatically classifies it as a “dangerous”.
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