Cybersecurity continues to be a critical aspect within every computing division, especially in the realm of operating system (OS) development. The OS resides at the lower layer above the hardware in the computing hierarchy. If the layers above the OS are well hardened, a security flaw in the OS will compromise the resources in those higher layers. Although several learning resources and courses are available for OS security, they are taught in advanced UG or graduate-level computer security classes. In this work, we develop cybersecurity educational modules that instructors can adoptin their OS courses to emphasize security in OS while teaching its concepts.
The goal of this work is to engage students in learning security aspects in OS, while learning its concepts. It will give students a good understanding of different security concepts and how they are implemented in the OS. Towards this, we develop security educational modules for an OS course that will be available to the instructors for adoption in their courses. These modules are designed to be used in a UG-level OS course. To work on these modules, students should be familiar with C programming and OS concepts taught in the class. The modules are intended to be completed within the course of a semester. To achieve this goal, we organize them into three mini-projects witheach can be completed within a few weeks. We chose xv6 as the platform due to its popularity as an educational OS for developing the modules.
To develop the modules, we referred to the recent version of a popular OS textbook for the security concepts. The topics discussed in it include authentication, authorization, cryptography, and distributed system security. We kept our educational modules mostly aligned with these topics except distributed system security. We also included a module for implementing a defense mechanism against buffer-overflow attacks, a famous software vulnerability. We created three mini-projects for these modules, each accompanied by proper documentation and a GitHub repository. Two versions are created for each project, one for a student’s assignment available in the repository and another as a solution version for instructors. The first project implements a user authentication system in xv6. Students will implement various specifications such as password structure with encryption and programs such as useradd, passwd, whoami, and login. The implementation guidelines are provided in the documentation, along with skeleton code. The authorization project implements the Unix-style access control system. In this project, students will modify and create various structures and functions within the xv6 kernel. The last project is to build a defense mechanism against buffer-overflow using Address Space Layout Randomization (ASLR). Students are expected to implement a random number generator and modify the executable file loader in xv6. The submission for each project is expected to demonstrate the module behavior comparable to relevant systems present in production grade OS, such as Linux.
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Student Teamwork on Programming Projects What can GitHub logs show us?
Teamwork, often mediated by version control systems such as Git and Apache Subversion (SVN), is central to professional programming. As a consequence, many colleges are incorporating both collaboration and online development environments into their curricula even in introductory courses. In this research, we collected GitHub logs from two programming projects in two offerings of a CS2 Java programming course for computer science majors. Students worked in pairs for both projects (one optional, the other mandatory) in each year. We used the students’ GitHub history to classify the student teams into three groups, collaborative, cooperative, or solo-submit, based on the division of labor. We then calculated different metrics for students’ teamwork including the total number and the average number of commits in different parts of the projects and used these metrics to predict the students’ teamwork style. Our findings show that we can identify the students’ teamwork style automatically from their submission logs. This work helps us to better understand novices’ habits while using version control systems. These habits can identify the harmful working styles among them and might lead to the development of automatic scaffolds for teamwork and peer support in the future.
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- Award ID(s):
- 1821475
- NSF-PAR ID:
- 10392590
- Date Published:
- Journal Name:
- Proceedings of The 13th International Conference on Educational Data Mining (EDM 2020)
- Page Range / eLocation ID:
- 409 - 416
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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