Anomaly Detection of Medical Data
This project addresses the critical problem of defining and identifying spurious data and news concerning COVID-19 and tracking the source of misinformation.
Attribute-Based Access Control
This project explores foundational and emerging challenges in modern access control by advancing the theory and practice of the NIST Next Generation Access Control (NGAC) model.
CPS Security and Resiliency
This project focuses on developing a framework with associated toolsets based on Machine Learning and AI Planning to analyze how a cyber-attack can trigger safety events in CPS and cascading failures and determine potential mitigations.
Energy Security
This project studies cyber-physical control and energy systems using the best tools and people available to ensure the safety of critical energy infrastructure.
Firmware Security
This project focuses on developing efficient testing techniques at the BIOS/Firmware level and developing robust protocols based on code signing and verification.
Heavy Vehicle Security
This project investigates security weaknesses of the SAE J1939 protocol stack and proposes practically deployable solutions to counter some of the impending threats.
IoT Security and Privacy
This project explores unique identification models and fine-grained access control models for IoT environments.
Mobile App Privacy
This project explores privacy-aware models and compliance assessment techniques for mobile health applications handling sensitive medical data.
Phishing Detection
Using different website features, we build a large labeled dataset and analyze several machine learning classifiers against this dataset to determine the most accurate in detecting phishing attacks.