Computer Science and Systems
Francisco Frade, fjfrade20sp@ollusa.edu
Our Lady of the Lake University, with Dr. Dietrich & Dr. Clark
Computer Information Systems and Security
Understanding the psychological impacts cyber-attacks have on employee’s
Cyber-attacks happen on a daily basis every second globally towards businesses. Threat actors intentionally attack this business in order to have financial gain or gather information for a much larger target. During these attacks internal user mistakes are normally the root cause for any attack occurring. This research investigates the emotional and behavioral impacts employees have after a cyber-attack. The data collected are from literature material such as a dissertation, blogs, case studies, and academic journals, using a meta-analysis approach with qualitative analysis. In the greater body of psychology and cybersecurity research, the lack of research focused in this area has a knowledge gap unknown to the field because of limited information publicly available. Most research provided approaches about what cyber-attacks can do, or the damage it can cause. However, none presents useful information for future research studies about developing human element response plans. The result of this study aims to convey needed response plans for employee’s, also known as end-users because there are few to none. Currently there are no results or findings yet for this interest. All information that’s gathered from the literature is planned to be used as evidence for this research results/findings.
Kevin Trinh, ktrinh1@mail.stmarytx.edu
St. Mary's University, with Dr. Art Hanna
Computer Science
Translating Custom Language to Assembly: A Python-Based Parser, Lexer, and Compiler
This project presents a Python-based implementation of a custom language parser, lexer, and compiler, aiming to provide a comprehensive toolset for translating code written in the custom language into assembly language for a virtual machine. By enabling execution on virtual hardware platforms, this project facilitates the development of domain-specific languages and their seamless execution. The project begins with designing and implementing a lexer module that identifies meaningful tokens by applying predefined grammar rules and regular expressions. Building on the lexer, the project constructs a parser module that generates an abstract syntax tree (AST), representing the hierarchical structure of the code. Next, the project implements a compiler module responsible for translating the AST into assembly language instructions for a virtual machine. The compiler incorporates optimization techniques to enhance efficiency and performance. To validate the toolset's effectiveness, a comprehensive set of test cases covers various grammar and semantic aspects of the custom language. These test cases ensure accurate translation and execution of custom language code into assembly language for the virtual machine using the parser, lexer, and compiler modules. This project demonstrates Python's versatility and power in developing language processing tools. It provides a comprehensive solution for translating custom language code into assembly language for a virtual machine, enabling seamless execution of domain-specific languages on virtual hardware platforms. The toolset's extensibility allows for future enhancements, including optimization techniques and support for diverse virtual machine architectures, expanding its utility and impact.