OPERATING SYSTEMS SECURITY

Course Description

This course covers both the fundamentals and advanced topics in operating system (OS) security. Access control mechanisms (e.g., SACL/DACL), memory protections, and interprocess communications mechanisms will be studied. Students will learn the current state-of-the-art OS-level mechanisms and policies designed to help protect systems against sophisticated attacks. In addition, advanced persistent threats, including rootkits and malware, as well as various protection mechanisms designed to thwart these types of malicious activities, will be studied. Advanced kernel debugging techniques will be applied to understand the underlying protection mechanisms and analyze the malicious software. Students will learn both hardware and software mechanisms designed to protect the OS (e.g., NX/ASLR/SMEP/SMAP).

OPERATING SYSTEMS SECURITY

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

No course outcomes have been defined yet.

Course Syllabus

Reference Books & Course Materials

1. 01 Operating System Security by Trent Jaeger, 3rd edition , 2022

Learning Outcomes

1. L01 Describe the fundamental principles and components of operating system security, including the role of the kernel, user accounts, and privilege levels. SOLO 3
2. L02 Configure and evaluate Unix/Linux security features such as file permissions, user management, access controls, and SELinux/AppArmor frameworks. SOLO 5
3. L03 Apply authentication and access control mechanisms, including password policies, Role-Based Access Control (RBAC), and Pluggable Authentication Modules (PAM). SOLO 4
4. L04 Assess the security implications of file systems and implement methods for securing data, including encryption, permissions, and file integrity monitoring. SOLO 4.5
5. L05 Identify and analyze common operating system threats and vulnerabilities, including privilege escalation, buffer overflows, and race conditions SOLO 3
6. L06 Demonstrate the use of host-based firewalls, such as iptables on Linux and Windows Firewall, to control and monitor network traffic. SOLO 4
7. L07 Design and evaluate homework-based security solutions with technical justification and peer collaboration. SOLO 5
8. L08 Implement secure shell (SSH) practices for remote access, key-based authentication, and tunneling to protect system communications. SOLO 4
9. L09 Create and develop operating system-level scripts that automate security tasks, audit logs, or user controls using Bash or PowerShell. SOLO 5
10. L10 Demonstrate applied knowledge of OS security through exam-based assessments and a final project presentation with documentation and practical demonstration SOLO 4

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