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This course covers fundamental security issues in computer communications, classical cryptographic algorithms, symmetric key cryptography (block and stream algorithms), public key cryptography (Diffie-Hellman, El Gamal, and elliptic curve cryptography), authentication, and digital signatures and other fundamental cryptographic primitives and protocols. These topics should be useful for those new to cybersecurity as well as those with some experience.

This course covers basic procedures of critical infrastructure protection. Object protection system will be analyzed. Classification of detection means and technical means of protection will be described. This course will also give information about various types of detectors.

This course will cover an overview and history of Java. Installing and configuring the development environment. Java basics: comments; data types; variables; operators. Introduction to classes and methods. Execution order management: blocks; conditional instructions; cycles. Instructions that violate the order of execution: multiple choice (switch). Arrays, rows. OOP paradigm, objects and object variables. Packages, exceptions. Graphical user interface and more.

This course covers methods and techniques how to protect network servers and endpoint computers against cyberthreats. The basics of network communications between various devices, like servers, PC, and routers, will be explained. Methods of secure communication, like VPN, IPsec, and VLAN will be examined. The course covers practical information about securing techniques of the database server, web server, mail server, DNS server, and file server securing techniques, reliable network devices configuration, protection of end-user devices, and monitoring of the health of devices.

This course focuses on the definition of current status of 5G networks. It will analyze core network architecture, radio access network, protocols, driving technologies, use cases, main procedures, cybersecurity subsystem, etc. Also attention will be paid to the analysis of research projects in the area, future research directions on the road to 6G.

The course is designed for a wide range of audience who, in the context of global informatization, must have the appropriate digital competencies for full-fledged activity as a subject of all world social processes. The security of personal data in the context of digitalization will be considered. Information on the security of interaction between state institutions in the provision of electronic services will also be considered. The use of electronic document management will be analyzed: electronic documents, signatures, stamps. Much attention will be paid to practical cases on electronic fraud in the modern digital world.

This course covers basic security systems for operating systems and application software tools. Course contains following topics:
⦁ data protection against unauthorized access;
⦁ data protection against copying;
⦁ data protection against destruction;
⦁ cryptographic data protection in different operating system;
⦁ software security of data transmission channels, etc.
The course will also cover the latest software protection services and tools.

This course focuses on the current advances and future directions in the research of machine learning technologies and their practical application. The main types of machine learning tasks in cybersecurity as well as the main types of machine learning models, such as linear, metric, probabilistic and other models, will be analyzed. The usage of decision trees, neural networks, and ensembles of decision rules in incident detection and threat categorization tasks will be covered. In addition, the course explains the process of machine learning experiments and the interpretation of their results in cybersecurity systems.

This course covers such topics: Basic concepts and terms of Big Data. The main advantages, problems and disadvantages of Big Data. Big Data Characteristics. Big data generation and processing technologies. Application in various fields. Data life cycle phases. Data storage, analysis and visualization. Visualization of texts, clusters, associations, hypotheses, decision trees. Multidimensional and grid visualization. Gephi classification. Machine learning and data mining. Big Data Infrastructure. Big Data Properties and Constraints. Interfaces. Cloud service models, cloud resources, cloud services. SQL and NoSQL databases. Big Data Management. Big Data Security. Tools and software for working with Big Data.

This course covers basic topics: Quantum Computing basic terms. The main directions of quantum informatics. Quantum objects, Fundamental feature of quantum objects, states. Moore’s Law. Shore and Grover algorithms. Qubit, superposition, spin, Quantum entanglement. Quantum cryptography, protocols and directions.