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TR

CYBER SECURITY-II

Course
ITSE202 - CYBER SECURITY-II
Department
Information Technology Security - English - Undergraduate
Course Type
Course
Status
Required
Language
Turkish
Credit
4
ECTS
0
T+P+L
3 + 0 + 2
Course Coordinator(s)
-
Prerequisite
-
Keywords

Course Description

The course aims to provide students with an in-depth understanding of the different types of malware and security breaches and to develop an effective prevention method that will increase overall security in the cyberspace. In this course, students are introduced to various monitoring techniques and protection procedures pertaining to security activities. Students also learn to apply these techniques practically. Topics covered in the course, includes an overview of cyber security infrastructure, cyber security management, wireless networking, organizational policy, information security policy, and defense in depth. At the completion of this course, student will understand the basic principles on how to build a secured computer networks and how to develop a valuable data asset, systems and processes.

CYBER SECURITY-II

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 Hadoop and HDFS
Week 3 HBase
Week 4 MapReduce and YARN
Week 5 Spark I
Week 6 Spark II
Week 7 Machine Learning and MLib
Week 8 Classification and Regression Algorithms I
Week 9 Classification and Regression Algorithms II
Week 10 Midterm(s)
Week 11 Unsupervised Learning Algorithms
Week 12 Recommender Systems & Collaborative Filtering
Week 13 Spark Streaming
Week 14 Data Visualization
Week 15 Final

Reference Books & Course Materials

No reference books have been listed.

Learning Outcomes

  1. L01 Explain the fundamental concepts, objectives, and importance of cybersecurity in organizational and real-world contexts. SOLO 4
  2. L02 Describe the principles and functions of network security, cryptography, hashing, and steganography in protecting information systems. SOLO 3
  3. L03 Identify and classify common cyber threats, cyberattack methods, malware-related risks, and social engineering techniques. SOLO 2.5
  4. L04 Apply appropriate security protocols, tools, and countermeasures to reduce vulnerabilities and protect computer systems and networks. SOLO 4
  5. L05 Analyze cybersecurity incidents and select suitable prevention, monitoring, and response strategies for organizational environments. SOLO 3.5
  6. L06 Perform basic penetration testing and digital forensic procedures to investigate security events and support evidence-based decision making. SOLO 4
  7. L07 Design a basic security solution or protection strategy to address organizational security needs and support safe system operation. SOLO 4
  8. L08 Evaluate cybersecurity practices in relation to professional, legal, and ethical responsibilities, including privacy, confidentiality, and data protection. SOLO 5

Program Outcomes

  1. P01 Apply data science principles and techniques to challenges in real life situations, and effectively communicate their solutions.
  2. P02 Identify and implement data analysis methodologies based on theoretical ideas, ethical code, and in-depth knowledge of the underlying data.
  3. P03 Analyze the guiding concepts and assessment procedures for information analysis in real-life applications.
  4. P04 Design and apply relevant data analysis models to find obscure solutions to business-related problems.
  5. 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.
  6. P06 Configure and administer the software tools required to efficiently produce usable information from any size of structured and unstructured datasets.
  7. P07 Administer or manage data science tools and techniques to organize and complete projects aimed at gaining useful insight from complex data.
  8. P08 Think critically and imaginatively, conceiving real-world issues from several angles, and work well in a variety of teams to solve issues cooperatively.
  9. 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
  10. 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.

Po-Lo Matrix

LO P01 P02 P03 P04 P05 P06 P07 P08 P09 P10 Average
L01 - - - - - - - - - - -
L02 - - - - - - - - - - -
L03 - - - - - - - - - - -
L04 - - - - - - - - - - -
L05 - - - - - - - - - - -
L06 - - - - - - - - - - -
L07 - - - - - - - - - - -
L08 - - - - - - - - - - -