Indrakshi Ray
Colorado State University-Fort Collins, CO·Computer Science
Mobile health apps on phones and smart devices collect sensitive personal health data. Users often cannot tell what data are collected, why, or whether the app follows privacy laws.
- Fields
Computer Science
- Topics
data privacy
privacy law
regulatory compliance
- Grants
- 1 known grant, through Sep 2027
What they work on
- Develop natural language processing models for cross-genre entailment that connect the meaning of privacy laws to technical software specifications, in order to identify privacy vulnerabilities in health data handling.
- Derive privacy constraints from identified vulnerabilities and build a formal privacy model designed to be complete, minimal and consistent.
- Analyze mobile health apps for conformity with the privacy model across the full data life cycle, combining large language models with domain-specific semantic similarity models.
- Build a framework that gives health app users fine-grained transparency and control over the personal data collected about them.
More about the research
Legal texts are hard for engineers and ordinary users to understand, and privacy protections are often missing from app design. This collaborative project aims to build a framework, called MedAn, that checks mobile health apps against privacy laws and gives users clearer information and finer control over their data.
Why it matters
Millions of people use mobile health apps that handle sensitive medical data. This work could help app developers build apps that comply with privacy law. It could help engineers and non-specialists understand legal privacy requirements. It could also give users clear information about what data an app collects and why, and more control over their personal health information.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Lavanya Elluri
Texas A&M University-Central Texas, TX·Computer Science
Develop a technique to automatically extract rules from U.S. IoT cybersecurity laws, data protection regulations and NIST standards, and store them in semantically rich ontologies built with Semantic Web technologies.
Zeyu Ding
Binghamton University, NY·Computer Science
Build automated tools that analyze an SQL database schema and help users interactively define a customizable privacy model specifying which data elements need differential-privacy protection, and which variant.
Milos Gligoric
University of Texas at Austin, TX·Computer Science
Develop a language and framework for writing fine-grained tests that check individual statements and code fragments inside functions, and evaluate it on open-source projects.
The school
Colorado State University-Fort Collins: 23 labs on PI Pages, $466M a year on research, 276 research doctorates a year.
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