CSEC528 MACHINE LEARNING DESIGN AND APPLICATION FOR CYBER SECURITY
| Course Code: | 9100528 |
| METU Credit (Theoretical-Laboratory hours/week): | 3(2-2) |
| ECTS Credit: | 8.0 |
| Department: | Cyber Security |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | |
| Offered Semester: | Fall and Spring Semesters. |
Course Content
This course aims to familiarize the cyber security and information systems students with data mining techniques and machine learning methods, with hands-on demonstrations on different cyber security use cases. The course will be conducted by first discussing the related concepts in theoretical formal lectures then applying sample codes in practical laboratory sessions.In the formal lectures, the concepts of artificial intelligence and data mining, such as data splitting & standardization, decision trees, linear & logistic regression, perceptron, support vector machines, naïve bayes, k-nearest neighbors, k-means, neural networks, self-organizing maps will be analyzed.
During the hands-on lab sessions, the discussed concepts & algorithms will be utilized in Python for different cyber security use cases. Several different Python libraries, code editing tools, and different datasets about phishing, virus signatures and network logs will be used. Using these datasets and discussed algorithms, sample tasks such as classification of anomalies, filtering spams, detecting malwares will be presented. The functions and methods in the employed libraries will also be discussed in the lab sessions.