Restricted Research - Award List, Note/Discussion Page
Fiscal Year: 2023
2405 The University of Texas at San Antonio (144293)
Principal Investigator: Bokaei Hosseini, Mitra
Total Amount of Contract, Award, or Gift (Annual before 2011): $ 125,962
Exceeds $250,000 (Is it flagged?): No
Start and End Dates: 3/1/21 - 2/29/24
Restricted Research: YES
Academic Discipline: SCIENCES
Department, Center, School, or Institute: Institute For Cyber Security
Title of Contract, Award, or Gift: Collaborative Research: SaTC: CORE: Medium: Narrowing The Gap Between Privacy Expectations and Reality in Mobile Health
Name of Granting or Contracting Agency/Entity:
National Science Foundation - NSF
CFDA Link: NSF
47.070
Program Title:
none
CFDA Linked: Computer and Information Science and Engineering
Note:
SAMs 1.1.1; The goal of this research project to design a multi-tiered automated information extraction approach for eliciting health data types and third-party entities from health apps' privacy policy text using natural language processing (NLP) techniques. The extracted information will be utilized in various ways, including (1) Detecting privacy violations between privacy policies and health app code data practices; (2) Analyzing the user's attitudes, opinions, preferences, and expectations about the legal protection of the data types collected by health apps; (3) Analyzing the compliance of health apps' privacy policies with regulations, such as GDPR, CCPA, and HIPAA. The project will advance the knowledge of automated privacy policy text analysis. For this reason, novel information extraction models will be produced to identify the health data and third-party entities in privacy policy text. Moreover, classification models will be designed to identify the semantic relationships between retrieved health data types and third-party entities. Finally, the semantic relations will be used to populate two knowledge bases which can further be used to briefly notify users on data practices, detect privacy violations, and validate apps' compliance with regulations. The datasets and models produced through this research will be publicly available. The project will expand research opportunities at UTSA as a minority-serving and Hispanic-serving (HSI) research-intensive institution in the South Texas region. This research will engage undergraduate and graduate students in scientific methods, privacy engineering, and NLP techniques.
Discussion: No discussion notes