Analytical methods of information security
Course: Network and internet technologies
Structural unit: Faculty of information Technology
Title
Analytical methods of information security
Code
ННД.07
Module type
Обов’язкова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
1 Semester
Number of ECTS credits allocated
5
Learning outcomes
Mastery of fundamental mathematical concepts used in cryptographic tools for information security is an important aspect of these skills. Understanding the basic types of cryptographic systems and the technologies involved in their design, implementation, and verification of correct functioning helps recognize and work with security systems. Proficiency in core algorithms that form the basis of cryptographic protection in information systems enables effective utilization for data security. Practical utilization of instrumental software tools for designing and developing software aids in creating secure systems. The ability to justify one's perspective on assigned tasks, communicate with colleagues regarding design and development issues, and produce written reports is crucial for efficient work in the field of cryptography.
Form of study
Full-time form
Prerequisites and co-requisites
Knowledge of the fundamentals of probability theory and mathematical statistics, basics of programming. Proficiency in skills: handling random variables and processes, evaluating system resilience to attacks, programming.
Course content
Within the course "Analytical Methods for Information Security," students are able to familiarize themselves with contemporary issues in information security and learn a software system that serves as a tool for solving such problems.
The course "Analytical Methods for Information Security" consists of the following sections: "Basic Concepts of the Python Language," "Autoregressive Models," "Moving Average Models," "SARIMA Models," "Markov Chains," and "Diffusion Processes." Each of these sections allows for the study of specific statistical methods for data analysis from both theoretical and practical perspectives, using the Python programming language as the software environment. Python is a powerful and widely-used programming language that is freely distributed worldwide and rapidly evolving through user contributions.
Recommended or required reading and other learning resources/tools
1. Hoffstein J., Pipher J., Silverman J. An introduction to mathematical cryptography. Springer, 2008.
2. Koblitz N. Algebraic aspects of cryptography. Algorithms and Computation in Mathematics. Berlin: Springer. ix, 206 p
3. Menezes, Alfred J.; van Oorschot, Paul C.; Vanstone, Scott A. Handbook of applied cryptography. CRC Press Series on Discrete Mathematics and its Applications. Boca Raton, FL: CRC Press. xxviii, 780 p.
Planned learning activities and teaching methods
Lectures, laboratory work, consultations, independent work.
Assessment methods and criteria
The level of achievement of all planned learning outcomes is determined based on the results of written assessments. The contribution of learning outcomes to the final grade, provided they have been mastered at an appropriate level, is as follows:
Assessment methods:
Semester assessment: The academic semester consists of one substantial module. The student must complete and pass seven laboratory works. The minimum requirement for eligibility to the exam is to accumulate at least 36 points throughout the semester.
Final assessment (in the form of an exam): The exam format is written and oral. The exam consists of 2 questions and 2 problems, each question being worth 10 points. The total score for the exam can range from 0 to 40 points. The condition for achieving a positive grade for the discipline is to obtain a minimum of 60 points, and the exam grade cannot be lower than 24 points.
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline