Assessment Of Two Pedagogical Tools For Cybersecurity Education

Cybersecurity is an important strategic areas of computer science, and a difficult discipline to teach effectively. To enhance and provide effective teaching and meaningful learning, we develop and assess two pedagogical tools: Peer instruction, and Concept Maps. Peer instruction teaching methodology has shown promising results in core computer science courses by reducing failure rates and improving student retention in computer science major. Concept maps are well-known technique for improving student-learning experience in class. This thesis document presents the results of implementing and evaluating the peer instruction in a semester-long cybersecurity course, i.e., introduction to computer security. Development and evaluation of concept maps for two cybersecurity courses: SCADA security systems, and digital forensics. We assess the quality of the concept maps using two well-defined techniques: Waterloo rubric, and topological scoring. Results clearly shows that overall concept maps are of high-quality and there is significant improvement in student learning gain during group-discussion

The Threat of Offensive AI to Organizations

AI has provided us with the ability to automate tasks, extract information from vast amounts of data, and synthesize media that is nearly indistinguishable from the real thing. However, positive tools can also be used for negative purposes. In particular, cyber adversaries can use AI to enhance their attacks and expand their campaigns. Although offensive AI has been discussed in the past, there is a need to analyze and understand the threat in the context of organizations. For example, how does an AI-capable adversary impact the cyber kill chain? Does AI benefit the attacker more than the defender? What are the most significant AI threats facing organizations today and what will be their impact on the future? In this study, we explore the threat of offensive AI on organizations. First, we present the background and discuss how AI changes the adversary’s methods, strategies, goals, and overall attack model. Then, through a literature review, we identify 32 offensive AI capabilities which adversaries can use to enhance their attacks. Finally, through a panel survey spanning industry, government and academia, we rank the AI threats and provide insights on the adversaries

Development of Peer Instruction Material for a Cybersecurity Curriculum

Cybersecurity classes focus on building practical skills alongside the development of the open mindset that is essential to tackle the dynamic cybersecurity landscape. Unfortunately, traditional lecture-style teaching is insufficient for this task. Peer instruction is a non-traditional, active learning approach that has proven to be effective in computer science courses. The challenge in adopting peer instruction is the development of conceptual questions. This thesis presents a methodology for developing peer instruction questions for cybersecurity courses, consisting of four stages: concept identification, concept trigger, question presentation, and development. The thesis analyzes 279 questions developed over two years for three cybersecurity courses: introduction to computer security, network penetration testing, and introduction to computer forensics. Additionally, it discusses examples of peer instruction questions in terms of the methodology. Finally, it summarizes the usage of a workshop for testing a selection of peer instruction questions as well as gathering data outside of normal courses

Computer Science 2019 APR Self-Study & Documents

UNM Computer Science APR self-study report and review team report for Spring 2019, fulfilling requirements of the Higher Learning Commission

A Holistic Analysis of Internet of Things (IoT) Security : Principles, Practices, and New Perspectives

Peer reviewedPublisher PD

Trustworthiness in Mobile Cyber Physical Systems

Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS

Towards Sustainable Blockchains:Cryptocurrency Treasury and General Decision-making Systems with Provably Secure Delegable Blockchain-based Voting

The blockchain technology and cryptocurrencies, its most prevalent application, continue to gain acceptance and wide traction in research and practice within academia and the industry because of its promise in decentralised and distributed computing. Notably, the meteoric rise in the value and number of cryptocurrencies since the creation of Bitcoin in 2009 have ushered in newer innovations and interventions that addressed some of the prominent issues that affect these platforms. Despite the increased privacy, security, scalability, and energy-saving capabilities of new consensus protocols in newer systems, the development and management of blockchains, mostly, do not reflect the decentralisation principle despite blockchains being decentralised and distributed in their architecture. The concept of treasury has been identified as a tool to address this problem. We explore the idea of blockchain treasury systems within literature and practice, especially with relation to funding and decision-making power towards blockchain development and maintenance. Consequently, we propose a taxonomy for treasury models within cryptocurrencies. Thereafter, we propose an efficient community-controlled and decentralised collaborative decision-making mechanism to support the development and management of blockchains. Our proposed system incentivises participants and is proven secure under the universally composable (UC) framework while also addressing gaps identified from our investigation of prior systems e.g. non-private ballots and insecure voting. Furthermore, we adapt our system and propose a privacy-preserving general decision making system for blockchain governance that supports privacy-centric cryptocurrencies. Besides, using a set of metrics, we introduce a consensus analysis mechanism to enhance the utility of decision-making of the systems by evaluating individual choices against collective (system-wide) decisions. Finally, we provide pilot system implementations with benchmark results confirming the efficiency and practicality of our constructions