The data breach phenomenon is not new. People have valued information, its protection, and its security for centuries. A data breach is the loss of control over one’s information. In contemporary society (circa 2024), a data breach can occur in several ways: through accidental disclosure, negligence, or malicious action. Likewise, the study of the data breach phenomenon is not new. As with other studies, this research effort seeks to expand the current body of knowledge concerning data breaches. However, unlike previous research, we adopt a novel approach to further our understanding of the phenomenon. By employing topological and phenomenological thinking, we have created a prototype allowing continuous, sustained, and scalable measurement of data breach intensity. Our data is derived from open sources, while the prototype application integrates both open and commercial applications. The goals of this study are to establish a process for collecting and storing data breach information using open sources; measure the intensity of data breaches based on stored open-source information; conduct statistical analysis of the data; present a novel instrument for measuring data breach intensity; and develop a prototype application that enables the storage, analysis, and measurement of data breaches. The research has successfully achieved its stated goals, demonstrating a thorough and comprehensive approach. First, a robust method of gathering and storing data breach event information was created. Second, an instrument to measure individual data breach event intensity was meticulously developed. Lastly, a prototype application was completed to store and analyze data breach events, ensuring a complete and detailed understanding of the data. Future research anchored to this manuscript is possible. The development of a new instrument allows for recursive study as well as forward-looking research efforts. For example, we can now recursively examine customer sentiment after a data breach event by examining the relationship between sentiment and intensity. Moreover, future research can discuss the cousins of data breach intensity (e.g., severity, density, and magnitude). However, there were some limitations to the research. The most glaring limitation was the inclusion of modifiers in the instrument. As discussed in more detail, these modifiers may have served better as modifiers or as a part of other equations (e.g., a severity equation).
","abstract_html":"<p>The data breach phenomenon is not new. People have valued information, its protection, and its security for centuries. A data breach is the loss of control over one’s information. In contemporary society (circa 2024), a data breach can occur in several ways: through accidental disclosure, negligence, or malicious action. Likewise, the study of the data breach phenomenon is not new. As with other studies, this research effort seeks to expand the current body of knowledge concerning data breaches. However, unlike previous research, we adopt a novel approach to further our understanding of the phenomenon. By employing topological and phenomenological thinking, we have created a prototype allowing continuous, sustained, and scalable measurement of data breach intensity. Our data is derived from open sources, while the prototype application integrates both open and commercial applications. The goals of this study are to establish a process for collecting and storing data breach information using open sources; measure the intensity of data breaches based on stored open-source information; conduct statistical analysis of the data; present a novel instrument for measuring data breach intensity; and develop a prototype application that enables the storage, analysis, and measurement of data breaches. The research has successfully achieved its stated goals, demonstrating a thorough and comprehensive approach. First, a robust method of gathering and storing data breach event information was created. Second, an instrument to measure individual data breach event intensity was meticulously developed. Lastly, a prototype application was completed to store and analyze data breach events, ensuring a complete and detailed understanding of the data. Future research anchored to this manuscript is possible. The development of a new instrument allows for recursive study as well as forward-looking research efforts. For example, we can now recursively examine customer sentiment after a data breach event by examining the relationship between sentiment and intensity. Moreover, future research can discuss the cousins of data breach intensity (e.g., severity, density, and magnitude). However, there were some limitations to the research. The most glaring limitation was the inclusion of modifiers in the instrument. As discussed in more detail, these modifiers may have served better as modifiers or as a part of other equations (e.g., a severity equation).</p>","abstract_has_math":false,"creators":["Palazzolo, James"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Open Access Dissertation","degree_discipline":"College of Engineering and Technology","degree_department":null,"school":null,"contributors":["Suleiman A. Ashur, PhD, Chair","Munther Abualkibash, PhD","Ola Karajeh, PhD"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-01-01T08:00:00Z","date_published":"2024-01-01T08:00:00Z","updated_at":"2026-07-24T02:17:53Z","subjects":["Cybersecurity","Information Security"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.emich.edu/theses/1322","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Suleiman A. Ashur, PhD, Chair","Munther Abualkibash, PhD","Ola Karajeh, PhD"]},{"key":"dc:creator","label":"Author","values":["Palazzolo, James"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2025-10-30T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["College of Engineering and Technology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Cybersecurity","Information Security"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.emich.edu/theses/1322"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The data breach phenomenon is not new. People have valued information, its protection, and its security for centuries. A data breach is the loss of control over one’s information. In contemporary society (circa 2024), a data breach can occur in several ways: through accidental disclosure, negligence, or malicious action. Likewise, the study of the data breach phenomenon is not new. As with other studies, this research effort seeks to expand the current body of knowledge concerning data breaches. However, unlike previous research, we adopt a novel approach to further our understanding of the phenomenon. By employing topological and phenomenological thinking, we have created a prototype allowing continuous, sustained, and scalable measurement of data breach intensity. Our data is derived from open sources, while the prototype application integrates both open and commercial applications. The goals of this study are to establish a process for collecting and storing data breach information using open sources; measure the intensity of data breaches based on stored open-source information; conduct statistical analysis of the data; present a novel instrument for measuring data breach intensity; and develop a prototype application that enables the storage, analysis, and measurement of data breaches. The research has successfully achieved its stated goals, demonstrating a thorough and comprehensive approach. First, a robust method of gathering and storing data breach event information was created. Second, an instrument to measure individual data breach event intensity was meticulously developed. Lastly, a prototype application was completed to store and analyze data breach events, ensuring a complete and detailed understanding of the data. Future research anchored to this manuscript is possible. The development of a new instrument allows for recursive study as well as forward-looking research efforts. For example, we can now recursively examine customer sentiment after a data breach event by examining the relationship between sentiment and intensity. Moreover, future research can discuss the cousins of data breach intensity (e.g., severity, density, and magnitude). However, there were some limitations to the research. The most glaring limitation was the inclusion of modifiers in the instrument. As discussed in more detail, these modifiers may have served better as modifiers or as a part of other equations (e.g., a severity equation).
"]},{"key":"dc:title","label":"Title","values":["A prototype application for the measurement of data breach event intensity"]}]}],"canonical_facts":{"dc:contributor":["Suleiman A. Ashur, PhD, Chair","Munther Abualkibash, PhD","Ola Karajeh, PhD"],"dc:creator":["Palazzolo, James"],"dc:date.available":["2025-10-30T07:00:00Z"],"dc:description.abstract":["The data breach phenomenon is not new. People have valued information, its protection, and its security for centuries. A data breach is the loss of control over one’s information. In contemporary society (circa 2024), a data breach can occur in several ways: through accidental disclosure, negligence, or malicious action. Likewise, the study of the data breach phenomenon is not new. As with other studies, this research effort seeks to expand the current body of knowledge concerning data breaches. However, unlike previous research, we adopt a novel approach to further our understanding of the phenomenon. By employing topological and phenomenological thinking, we have created a prototype allowing continuous, sustained, and scalable measurement of data breach intensity. Our data is derived from open sources, while the prototype application integrates both open and commercial applications. The goals of this study are to establish a process for collecting and storing data breach information using open sources; measure the intensity of data breaches based on stored open-source information; conduct statistical analysis of the data; present a novel instrument for measuring data breach intensity; and develop a prototype application that enables the storage, analysis, and measurement of data breaches. The research has successfully achieved its stated goals, demonstrating a thorough and comprehensive approach. First, a robust method of gathering and storing data breach event information was created. Second, an instrument to measure individual data breach event intensity was meticulously developed. Lastly, a prototype application was completed to store and analyze data breach events, ensuring a complete and detailed understanding of the data. Future research anchored to this manuscript is possible. The development of a new instrument allows for recursive study as well as forward-looking research efforts. For example, we can now recursively examine customer sentiment after a data breach event by examining the relationship between sentiment and intensity. Moreover, future research can discuss the cousins of data breach intensity (e.g., severity, density, and magnitude). However, there were some limitations to the research. The most glaring limitation was the inclusion of modifiers in the instrument. As discussed in more detail, these modifiers may have served better as modifiers or as a part of other equations (e.g., a severity equation).
"],"dc:identifier":["https://commons.emich.edu/theses/1322"],"dc:subject":["Cybersecurity","Information Security"],"dc:title":["A prototype application for the measurement of data breach event intensity"],"thesis:degree_discipline":["College of Engineering and Technology"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T02:17:53Z"}