Research presented at the 31st USENIX Security Symposium in August included auditing of network traffic and privacy policies in Oculus Virtual Reality (OVR), ML-based approaches to detect ad and tracking request chains and a novel graph manipulation evasion technique, and the design of a minimal active ROT for low-end MCU-s.
Project scientist, Rahmadi Trimananda (UC Irvine) presented “OVRseen: Auditing Network Traffic and Privacy Policies in Oculus VR”, the first comprehensive analysis of personal data exposed by OVR apps and the platform itself. This is collaborative work within PI Markopoulou’s group.
Graduate student, Esmerald Aliaj (UC Irvine) presented “GAROTA: Generalized Active Root-Of-Trust Architecture ” which explores how embedded devices are targets for exploits and malware. This is collaborative work within co-PI Tsudik’s group.
Post doctorate scholar, Umar Iqbal (University of Washington) presented “Khaleesi: Breaker of Advertising and Tracking Request Chains“, a machine learning approach that captures the essential sequential context needed to effectively detect advertising and tracking request chains. This is collaborative work within PI Shafiq’s group.
Graduate student, Sandra Siby (EPFL,) presented “WebGraph: Capturing Advertising and Tracking Information Flows for Robust Blocking“, the first ML-based ad and tracker blocking approach that does not rely on content features. This is collaborative work within PI Shafiq’s group.
See all papers on our publications page.