Adversarial

Fundamentals Computer Science: Adversarial Computing

Need for Cybersecurity Concepts in Software Development

There is a national deficiency in software developers possessing adversarial thinking abilities is evident within the field of computing. This scarcity has created a disconnect between Career Technical Education (CTE) and Academic Degrees. On one hand, many IT professionals who come from CTE programs have a strong grasp of cybersecurity, including areas like forensics, intrusion detection systems, firewalls, and networks, but they lack essential software development skills. Conversely, computer scientists and developers with academic degrees excel in software development but often lack crucial adversarial thinking skills. Consequently, there is a pressing demand for software developers who combine adversarial thinking abilities with the capacity to design, develop, and implement secure software, thereby fortifying organizational computing systems.

Adversarial Thinking is the Computational Thinking++

In the context of the Cybersecurity Curricular Guidelines (CSEC 2017) [1], Adversarial Thinking is recognized as a foundational concept that permeates various domains within the cybersecurity curriculum. However, given the evolving landscape of computer science education, including the integration of emerging fields like cybersecurity sciences, the appeal of teaching this concept across all computing disciplines varies. One specific course, often referred to as Fundamentals of Computer Science or CS 1, is offered in both two-year and four-year educational institutions. This course caters not only to computer science majors but also to students pursuing computing-related degrees such as data analytics, cybersecurity, data science, or various CS + X programs. The CS 1 has become a cornerstone for many computing disciplines in contemporary education. Given the widespread popularity of CS 1, there exists a demand to introduce concepts that extend beyond basic computational thinking. In this paper, we put forth the notion of Adversarial Thinking, a concept that, when coupled with computational thinking, can equip future programmers with the skills to consider risk analysis at every stage of code development.

The Contribution

The xAI Institute at El Paso Community College actively is researching the identification of adversarial thinking concepts within the core fundamentals of computer science. In this paper, we delve into the aspects related to CS 1.

References

[1] Joint Task Force on Cybersecurity Education. Cybersecurity Curricula 2017: Curriculum Guidelines for Post-Secondary Degree Programs in Cybersecurity. Association for Computing Machinery, New York, NY, USA, 2018.

Work presented at the 30th Joint UTEP/NMSU Workshop on Mathematics, Computer Science, and Computational Sciences University of Texas at El Paso. El Paso, Texas. Saturday, October 28, 2023

Misinformation Analytics

Adversarial thinking refers to a mindset or approach that involves actively considering potential threats, weaknesses, or opposing viewpoints when analyzing a situation, making decisions, or solving problems. This approach is often used in various fields, including business, technology, security, and even personal decision-making. The goal of adversarial thinking is to anticipate and understand potential challenges or criticisms that may arise in a given scenario. By actively seeking out weaknesses or vulnerabilities, individuals or teams can better prepare for potential risks and develop more robust solutions. Adversarial thinking is particularly important in areas such as cybersecurity, where anticipating and defending against potential attacks is crucial. In this project, we will explore scenarios aimed at addressing situations involving adversarial decision-making. The project encompasses two primary concentrations: cybersecurity and analytics, and an educational component. In the cybersecurity and analytics focus, our attention will be on studying the concept of misinformation and its real-world implications. Misinformation, as a form of adversarial thinking, has the potential to alter critical decisions based on premises and information lacking factual support. The project's objective is to identify situations where misinformation can have a substantial impact and to model them using established statistical/adversarial frameworks to devise effective solutions.

The educational component of the project will delve into pedagogical aspects related to disseminating concepts of adversarial thinking in introductory computer science courses, such as CS 1, 2, and 3. We aim to develop effective strategies for teaching and integrating adversarial thinking concepts within these foundational courses.

Through these dual concentrations, our project aims to contribute valuable insights into both practical applications in cybersecurity and analytics, as well as effective educational approaches for fostering a deeper understanding of adversarial thinking in computer science curricula.

Bloom's Verbs to Enhance Adversarial Mindset

Adversarial Thinking stands out as a pervasive concept with broad applications in the realm of cybersecurity. Meeting the escalating demand for cybersecurity training within the workforce has emerged as a significant goal for numerous computing programs, particularly at the two- and four-year academic levels. The utilization of Bloom's Taxonomy in education has been widespread, primarily for organizing curriculum learning outcomes, competencies, assessments, and activities. The application of Bloom's for Computing involves a compilation of verbs specifically tailored to computing, emphasizing active engagement in considering computing aspects when formulating learning outcomes. In this study, we introduce a collection of active verbs and examples of learning outcomes specifically curated for introductory computing courses, aimed at enhancing Adversarial Thinking.