DATA AND NETWORK SECURITY
- Course
- ITSE479 - DATA AND NETWORK SECURITY
- Department
- Information Technology Security - English - Undergraduate
- Course Type
- Course
- Status
- Required
- Language
- Turkish
- Credit
- 3
- ECTS
- 0
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- -
- Prerequisite
Course Description
This course discusses different types of malicious attacks and various methods of mitigating to them. Students learn how to protect computer networks by using security codes. Topics covered includes foundations of network security, IP packet structure and analysis control, routing and access control lists, attack techniques, network defense fundamentals, sign-on solutions and file encryption solutions. At the end, the course students will be able to understand the security problems introduced by the combination of the Internet with Intranets, mobile devices, and sensors networks. Students will also be able to develop a basic understanding of the theoretical and conceptual aspects that are needed to build secure systems.
DATA AND NETWORK SECURITY
Evaluation Tools (Active Term)
No evaluation items have been defined.
Course outcomes
No course outcomes have been defined yet.
Course Syllabus
| Week | Topic |
|---|---|
| Week 1 | Introduction |
| Week 2 | Data and Network Treats and Attacks |
| Week 3 | Sql Injection Attack |
| Week 4 | Cross-site scripting |
| Week 5 | Homework1 Presentation |
| Week 6 | API7:2023 - Server Side Request Forgery |
| Week 7 | Cross-site request forgery (CSRF) |
| Week 8 | API2:2023 Broken Authentication |
| Week 9 | Homework2 Presentation |
| Week 10 | API1:2023 - Broken Object Level Authorization |
| Week 11 | API9:2023 - Improper Inventory Management |
| Week 12 | Project Presentation |
| Week 13 | Project Presentation |
| Week 14 | Project Presentation |
| Week 15 | Fınal Exam |
Reference Books & Course Materials
- 01 SQL Injection Attacks and Defense BY Justin Clarke
Learning Outcomes
No learning outcomes have been defined.
Program Outcomes
- P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
- P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
- P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
- P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
- P05 Utilize modern computing techniques to handle real-world problems characterized by massive amounts of data, such as parallel and distributed computing and machine learning.
- P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
- P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
- P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
- P09 Be able to effectively integrate data‐based solutions into the user environment and help non-technical professionals in exploring, visualizing, and using these solutions
- P10 Understand their obligations under professional and ethical standards in relation to matters like data ownership and citation, data security and sensitivity and the privacy implications of data analysis.
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