Engineering Commons^™

Quantifying Cyber Risk By Integrating Attack Graph And Impact Graph, Omer F. Keskin

Engineering Management & Systems Engineering Theses & Dissertations

Being a relatively new risk source, models to quantify cyber risks are not well developed; therefore, cyber risk management in most businesses depends on qualitative assessments. With the increase in the economic consequences of cyber incidents, the importance of quantifying cyber risks has increased. Cyber risk quantification is also needed to establish communication among decision-makers of different levels of an enterprise, from technical personnel to top management.

The goal of this research is to build a probabilistic cybersecurity risk analysis model that relates attack propagation with impact propagation through internal dependencies and allows temporal analysis.

The contributions of the developed …

Cybersecurity Risk Assessment Using Graph Theoretical Anomaly Detection And Machine Learning, Goksel Kucukkaya

Engineering Management & Systems Engineering Theses & Dissertations

The cyber domain is a great business enabler providing many types of enterprises new opportunities such as scaling up services, obtaining customer insights, identifying end-user profiles, sharing data, and expanding to new communities. However, the cyber domain also comes with its own set of risks. Cybersecurity risk assessment helps enterprises explore these new opportunities and, at the same time, proportionately manage the risks by establishing cyber situational awareness and identifying potential consequences. Anomaly detection is a mechanism to enable situational awareness in the cyber domain. However, anomaly detection also requires one of the most extensive sets of data and features …

Systemic Analysis Of The Use Of Artificial Intelligence (Ai) In Regulating Terrorist Content On Social Media Ecosystem Using Functional Dependency Network Analysis (Fdna), Alaina Roman, C. Ariel Pinto

OUR Journal: ODU Undergraduate Research Journal

This research is a systemic analysis of emerging risks to the use Artificial Intelligence (AI) in regulating terrorist content on social media ecosystems using Functional Dependency Network Analysis (FDNA), a proven system-design-and-analysis tool). The research has three phases: 1) framing the problem by identifying and describing AI ecosystem elements as intended, implied and explicit objectives, discernible attributes, and performance indictors; 2) describing the idealized problem-solved scenario, which includes detailing ‘success’ states of the ecosystem; and 3) systemic risk analysis including identifying failure scenarios for each element and establishing causalities among elemental attributes leading to failure scenarios. This research contributes toward …