Cybersecurity Science with Shawn Riley

I. Introduction Over the last decade, the cybersecurity industry has predominantly relied on quantitative analysis of historical data to measure and manage cyber risk. While this approach is useful in understanding past trends and patterns in cyber attacks, it may not provide an accurate reflection of the current threat landscape. The Digital Cyber Twin (DCT) approach offers a unique and innovative solution to support ongoing cyber risk assessment and decision-making by focusing on the present state rather than historical data. Through the use of automation, machine reasoning, and the scientific method, the DCT approach provides a more accurate and up-to-date view of an organization's security posture. By continuously collecting and analyzing various types of data, the DCT approach allows for the identification of emerging threats and the implementation of mitigation strategies. This approach is different from traditional quantitative analysis that focuses on historical data and ma

Interoperability is a crucial aspect of cybersecurity science that enables various systems, applications, and technologies to securely exchange information and communicate with each other. Common Language is a core theme of cybersecurity science that aims to establish a consistent and reliable language to express the security aspects of system architecture, risk assessments, and core principles such as trust relocation. Interoperability is critical to achieving this goal. Interoperability can be divided into four levels, namely foundational, structural, semantic, and organizational. The foundational level is the basic level of interoperability, which establishes interconnectivity between different systems and enables basic data exchange services. At this level, the focus is on establishing a common language for communicating data, which enables two systems to communicate with each other. This level is critical in cybersecurity science, as it allows systems to communicate with each othe

Cyber Defense Analysts (PR-CDA-001) are professionals who analyze events occurring in their environments using data collected from various cyber defense tools, such as firewalls, network traffic logs, and IDS alerts. The purpose of their analysis is to identify and mitigate any threats to the system. The abilities required for this work role include the ability to analyze malware and conduct vulnerability scans to identify vulnerabilities in security systems. They must have the ability to apply cybersecurity and privacy principles to organizational requirements such as confidentiality, integrity, availability, authentication, and non-repudiation. They must also be able to interpret the information collected by network tools, such as Nslookup, Ping, and Traceroute, and accurately and completely source all data used in intelligence, assessment, and/or planning products. Cyber Defense Analysts must have knowledge of computer networking concepts and protocols, risk management processes, cy

Introduction: In today's world, the demand for STEM skills is growing rapidly, making it essential to provide a STEM education that focuses on building scientific reasoning and argumentation skills. One promising approach to STEM education is Argument-Driven Inquiry (ADI), which emphasizes the construction and defense of scientific claims based on scientific reasoning and data analysis. ADI has been used in various STEM courses from grade school to university levels to promote deeper understanding of scientific concepts and practices. Additionally, ADI can be applied in real-world contexts by STEM professionals to investigate complex phenomena, from subatomic particles to financial markets, and develop evidence-based solutions. In this paper, we will explore the use of ADI in STEM education and its real-world applications. We will also discuss how ADI can benefit employees by improving their problem-solving, decision-making, innovation, collaboration, and adaptability skills. ADI i

As the threat landscape of cybersecurity continues to evolve, organizations must keep pace with the latest technologies and solutions to protect themselves against attacks. However, with so many options available, selecting the right cybersecurity technology can be a challenging task. That's where the framework of argument-driven inquiry (ADI) can be helpful. ADI is a problem-solving framework used in science education to help students develop critical thinking skills. It can also be applied to cybersecurity to help organizations select new technologies. The seven steps of ADI can guide organizations through the process of selecting the right cybersecurity technology: Identify a problem: The first step is to identify the problem that the organization is trying to solve. For example, the problem could be that the current security solution is not providing adequate protection against the latest threats. Develop a question: Once the problem has been identified, the next step is to dev

Artificial intelligence (AI) has been touted as the solution to a wide range of problems, from fraud detection to healthcare. However, the reality is that AI is not a silver bullet, and not all AI approaches are equal. One of the key limitations of machine learning, which has been the dominant AI approach in recent years, is that it can only operate on data that is already labeled or annotated. This means that machine learning algorithms can only detect patterns and associations that are already known. To go beyond this, AI needs to incorporate knowledge representation and reasoning to enable it to reason about the world and draw conclusions based on that reasoning. Machine learning has been the dominant AI approach in recent years, and it has been used to great effect in a wide range of applications. However, its limitations are becoming increasingly apparent. One of the key limitations of machine learning is that it requires labeled data to learn from. This means that machine learnin

As the complexity and volume of data in the cybersecurity landscape continue to grow, the need for effective data management and sharing has become increasingly important. Traditional cybersecurity solutions have focused on the foundational and structural levels of interoperability, which involve integrating different technologies and systems to enable data exchange. However, the rise of semantic interoperability in cybersecurity is leading to a paradigm shift in how data is managed, shared, and analyzed. Semantic interoperability refers to the ability of different systems and applications to exchange information and understand it in a common language. It involves creating a shared vocabulary and set of rules for describing data, which enables machines to exchange and understand information in a more efficient and accurate manner. This approach is revolutionizing the way cybersecurity is done, and it has many benefits for risk assessment in particular. Risk assessment is an essential p

I. Introduction A. Background on Integrated Adaptive Cyber Defense (IACD) The rapid advancement of technology and the increasing interconnectedness of digital systems have led to an ever-increasing threat of cyber attacks. As the complexity and frequency of these attacks continue to rise, traditional cyber defense methods have proven to be insufficient. To address these challenges, a new approach to cybersecurity has emerged: Integrated Adaptive Cyber Defense (IACD). IACD is a holistic approach to cybersecurity that emphasizes an integrated and adaptive response to cyber threats. It combines advanced technologies, such as artificial intelligence and automation, with human expertise to create a dynamic defense system. IACD is designed to be adaptable and flexible, allowing it to respond to the evolving threat landscape and provide effective protection against a wide range of cyber attacks. B. Importance of IACD in today's cyber threat landscape The current cyber threat landscape is