Author ORCID Identifier

https://orcid.org/0000-0002-2676-1487

Date of Award

2025

Document Type

Thesis (Ph.D.)

Department or Program

Computer Science

First Advisor

Sean W Smith

Second Advisor

Sergey Bratus

Third Advisor

Shagufta Mehnaz

Abstract

Given the growing amount and variety of data handled by modern systems, it is crucial to guarantee the accuracy and protection of input data without errors or malicious intentions. The need to improve security in software programs often conflicts with the assurance of maximum performance, making developers and maintainers hesitant to incorporate more testing.

LangSec (Language-Theoretic Security) is a security approach that treats input validation as a formal language recognition problem, ensuring that only well-defined, unambiguous inputs are processed to eliminate exploitable parsing flaws. This dissertation explores integrating LangSec principles with Pareto optimization to enhance safety and robustness in digital environments. We introduce three novel methods for embedding LangSec techniques into software applications and data streams, striking a balance between security and performance. These approaches offer practical, adaptable solutions for improving the security and efficiency of existing software and network protocols, advancing the resilience of modern computing systems.

Download

Share

COinS