| Course Title | Code | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|
| Artificial Intelligence in Cyber Security | SG525 | 3 + 0 | 3.0 | 8.0 |
| Prerequisites | None |
| Language of Instruction | Turkish |
| Course Level | Graduate |
| Course Type | |
| Mode of delivery | The course is given over the weekly presentation files. In addition, it is carried out in the form of presentations by students on certain topics. After the theory is given with the presentation, applications are also made after the midterm exam. |
| Course Coordinator | |
| Instructors | |
| Assistants | |
| Goals | Students are given competencies within the scope of cyber security, which is expected to have at the international level today. In addition, it is to prepare students for topics such as cyber security standards and compliance, network security, security of mobile devices, and cyber security risk management. |
| Course Content | Cyber Security Standards and Compliance, Applied Network Security, Application Security Principles / Practices, Cyber Operational Planning, Software Security, Cyber Security Risk Management and Compliance, Mobile Device Management, Secure Unix Management, End User Device Security and IoT, Security of Machine Learning Models, Artificial Intelligence Applications in Cyber Security. |
| Learning Outcomes |
- Learns the use of artificial intelligence in cyber security. - Can apply artificial intelligence in the field of cybersecurity. |
| Week | Topics | Learning Methods |
|---|---|---|
| 1. Week | Cyber Security Standards and Compliance | |
| 2. Week | Applied Network Security | |
| 3. Week | Applied Network Security | |
| 4. Week | Application Security Policies / Practices | |
| 5. Week | Application Security Policies / Practices | |
| 6. Week | Cyber Operational Planning | |
| 7. Week | Software Security | |
| 8. Week | Cyber Security Risk Management and Compliance | |
| 9. Week | Mobile Device Management | |
| 10. Week | Secure Unix Management | |
| 11. Week | Secure Unix Management | |
| 12. Week | End User Device Security | |
| 13. Week | Security of IoT, Machine Learning Models | |
| 14. Week | Implementing Artificial Intelligence in the Field of Cyber Security |
| Internet of Things and Cyber Physical Systems_ Security and Forensics |
| Cyber Deception_ Techniques, Strategies, and Human Aspects |
| Cyber Security Applications for Industry 4.0 |
| Program Requirements | Contribution Level | DK1 | DK2 | Measurement Method |
|---|
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| Course's Level of contribution | None | Very Low | Low | Fair | High | Very High |
| Method of assessment/evaluation | Written exam | Oral Exams | Assignment/Project | Laboratory work | Presentation/Seminar |
| Event | Quantity | Duration (Hour) | Total Workload (Hour) |
|---|---|---|---|
| Midterm 1 | 1 | 10 | 10 |
| Homework 1 | 2 | 20 | 40 |
| Final | 1 | 20 | 20 |
| Practice | 1 | 10 | 10 |
| Classroom Activities | 10 | 2 | 20 |
| Total Workload | 100 | ||
| ECTS Credit of the Course | 8.0 | ||
