Towards Automating the Generation of Finite State Machines from Natural Language Specifications: A Focus on Cellular Network Security
Open Access
Author:
Ishtiaq, Abdullah Al
Graduate Program:
Computer Science and Engineering
Degree:
Master of Science
Document Type:
Master Thesis
Date of Defense:
February 19, 2024
Committee Members:
Syed Rafiul Hussain, Thesis Advisor/Co-Advisor Rui Zhang, Committee Member Chitaranjan Das, Program Head/Chair
Keywords:
Cellular Network Security Natural Language Processing Formal Analysis Finite State Machines Cellular Network Security Natural Language Processing Formal Analysis Finite State Machines
Abstract:
In this work, we present Hermes, an end-to-end framework to automatically generate formal representations from natural language cellular specifications. We first develop a neural constituency parser, NEUTREX, to process transition-relevant texts and extract transition components (i.e., states, conditions, and actions). We also design a domain-specific language to translate these transition components to logical formulas by leveraging dependency parse trees. Finally, we compile these logical formulas to generate transitions and create the formal model as finite state machines. To demonstrate the effectiveness of Hermes, we evaluate it on 4G NAS, 5G NAS, and 5G RRC specifications and obtain an overall accuracy of 81-87%, which is a substantial improvement over the state-of-the-art. Our security analysis of the extracted models uncovers 3 new vulnerabilities and identifies 19 previous attacks in 4G and 5G specifications, and 7 deviations in commercial 4G basebands.
