Hai Phan

Associate Professor

hai.phan@njit.edu

Research Areas: Social network analysis, machine learning, spatio-temporal data mining

Preserving Sensitive Health Care Data

Networks that share electronic health records containing a patient’s personal and clinical data promise improved continuity of care and better health outcomes. However, these networks put highly sensitive patient information at risk and expose healthcare providers to legal jeopardy. We created DeepPrivate, a system that uses machine learning techniques to protect personal health information against cyber attacks.

Cristian Borcea

Professor

borcea@njit.edu

Research Areas: Privacy, online advertising

Online Publishers Compliance with Privacy Regulations

Privacy regulations are enacted by governments around the world to protect their citizens. The most well-known such regulation is the General Data Protection Regulation (GDPR), for protecting European Union (EU) citizens from unnecessary and unauthorized personal data collection. We studied GDPR compliance under the Transparency and Consent Framework (TCF), which is widely used across the Internet and provides digital advertising market participants a standard for sharing users’ privacy consent choices. We found that most websites properly record the user’s consent choice, but over 72% of the websites that were TCF compliant claimed legitimate interest as a rationale for overriding the consent choice. While legitimate interest is legal under GDPR, using it at large scale contradicts the spirit of the law. Additionally, analysis of cookies set to the browsers indicates that TCF may not fully protect user privacy even when websites are compliant.