Cybersecurity attacks such as phishing, malware, and ransomware have become a major concern in recent years, with many individuals and organizations suffering financial losses as a result. Most people are unaware of the different types of cybersecurity attacks and have not seen examples of them. To address this problem, we developed the Cybersecurity Management System: Defense and Response (CMSDR) cloud software application. It provides both the "Defense" and "Response" to cybersecurity attacks, with educational materials and examples to help users learn about different types of cybersecurity attacks, and a computer-aided reporting and notification system to help organizations respond to ongoing incidents. CMSDR is a universal application that can be used on any platform with a web browser. Any company or organization can effectively run CMSDR on their own server computer for cybersecurity defense and response. / Master of Science / Cybersecurity has become a major concern in recent years as many individuals and organizations have suffered financially from cybersecurity attacks like phishing, malware, and ransomware. This thesis seeks to provide a solution to the emerging number of cybersecurity breaches by introducing Cybersecurity Management System: Defense and Response (CMSDR) cloud software application that features "Defense" and "Response" to cybersecurity attacks. For "Defense", it aims to guide the users of the common types of cybersecurity attacks following the pedagogy "Learning by Examples" by providing cybersecurity examples to support the learning. For "Response", it aims to provide a system that features computer-aided reporting and notification of cybersecurity breaches in a company or organization. The software application is universally usable on any platform with a web browser. With the help of CMSDR, users receive proper education of the types of cybersecurity attacks to raise awareness. Organizations can report and notify ongoing cybersecurity breach incidents to their members easily and effectively.
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/113291 |
Date | 19 January 2023 |
Creators | Huang, Chenxiang |
Contributors | Computer Science and Applications, Balci, Osman, Barkhi, Reza, Seyam, Mohammed Saad Mohamed Elmahdy |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Language | English |
Detected Language | English |
Type | Thesis |
Format | ETD, application/pdf, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0019 seconds