Subject

Application of Machine Learning in Information Security

Course Title

Application of Machine Learning in Information Security
Application of Machine Learning in Information Security

Code

m23_w_052

Study Programme

—

Organizer of the study programme (unit, institute, department or division)

Faculty of Computer Science and Engineering

Degree level (first, second, third cycle)

Second cycle

Academic year / semester

9 / Winter

Number of ECTS credits

Teacher

Александра Поповска Митровиќ, Христина Михајлоска Трпческа, Весна Димитрова

Prerequisites for enrolling in the course

—

10.

Objectives of the course programme (competences)

Целта на предметот е примена на машинско учење низ примери од областа на безбедноста на информациите и илустрација на употребата на различни техники за учење во јасни сценарија.

11.

Course content

Анализа на методи од машинско учење и примена на соодветен метод за решавање на проблеми поврзани со информациска безбедност. Анализа на резултатите добиени со методи од машинско учење и наоѓање на решенија за подобрување на истите со користење на разни карактеристики на методите и алгоритмите.

12.

Learning methods

Lectures, projects, discussions and workshops

13.

Total available time

6 ECTS x 30 hours = 180 hours

14.

Distribution of available time

60 + 0 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.	Lectures - theoretical instruction	60 hours
15.2.	Exercises (laboratory, auditory), seminars, teamwork	0 hours

16.

Other forms of activities

16.1.	Project assignments	45 hours
16.2.	Independent assignments	45 hours
16.3.	Home study	30 hours

17.

Assessment method

17.1.	Tests	0 points
17.2.	Seminar paper / project (presentation: written and oral)	45 points
17.3.	Activities and learning	20 points
17.4.	Final exam	50 points

18.

Grading criteria (points / grade)

up to 50 points	5 (five) (F)
from 51 to 60 points	6 (six) (E)
from 61 to 70 points	7 (seven) (D)
from 71 to 80 points	8 (eight) (C)
from 81 to 90 points	9 (nine) (B)
from 91 to 100 points	10 (ten) (A)

19.

Requirement for obtaining a signature and taking the final exam

Homework

20.

Language of instruction

Macedonian and English

21.

Method for monitoring the quality of teaching

Internal Evaluation and Survey Mechanism

22.

Literature

22.1.	Required literature 1. M. Stamp \| Introduction to Machine Learning with Applications in Information Security \| 2023 2. C. Chio, D. Freeman \| Machine Learning and Security \| 2018
22.2.	Additional literature No. Author Title Publisher Year