IoT deployments collect enormous amounts of sensor data, but making use of it still requires knowing which sensors to query, which machine learning models to run, and how to stitch the results together — expertise most organizations do not have.
Detecting malicious Bluetooth Low Energy (BLE) trackers remains challenging because existing approaches rely on fixed time and distance thresholds that are brittle across environments. These heuristics produce false positives in dense environments …
Given the pervasiveness of Bluetooth Low Energy (BLE)-based devices, detecting unwanted or suspicious trackers is challenging, especially due to their heterogeneity, cross-platform compatibility issues, and inconsistent detection methods. BL(u)E CRAB …
Long queues in retail and public environments can frustrate customers and negatively impact user experiences. Traditional camera-based monitoring systems are effective in analyzing queues, however, the potential for identification raises privacy …
Several of the group’s systems are deployed and evaluated on UMBC’s campus, which doubles as a living testbed for research on IoT data management and privacy. This page collects that campus-deployment work; new deployments are added here as they are published.
Smart devices talk to the network far more than their users expect, and the traffic they generate reveals a lot: which services they contact, how often, and what they do when nobody is using them.
The constant connectedness of smart home devices and their sensing capabilities pose a unique threat to individuals' privacy. While users may expect devices to exhibit minimal activity while they are not performing their intended functions, this is …
In smart spaces, data flows from sensors through data processing pipelines that interpret and enrich it to realize the needs of diverse applications. Smart space data may also be stored for future analysis and processing to implement new …
Website privacy policies are often lengthy and intricate. Privacy assistants assist in simplifying policies and making them more accessible and user-friendly. The emergence of generative AI (genAI) offers new opportunities to build privacy assistants …
Privacy policies are the main channel through which organizations tell people what happens to their data, yet they are long, intricate, and routinely skipped or misunderstood — and for smart devices they are scattered across manufacturers and e-commerce platforms, so even finding the right policy is hard.