Weikeng Chen (UC Berkeley), Raluca Ada Popa (UC Berkeley)

File-sharing systems like Dropbox offer insufficient privacy because a compromised server can see the file contents in the clear. Although encryption can hide such contents from the servers, metadata leakage remains significant. The goal of our work is to develop a file-sharing system that hides metadata---including user identities and file access patterns.

Metal is the first file-sharing system that hides such metadata from malicious users and that has a latency of only a few seconds. The core of Metal consists of a new two-server multi-user oblivious RAM (ORAM) scheme, which is secure against malicious users, a metadata hiding access control protocol, and a capability sharing protocol.

Compared with the state-of-the-art malicious-user file-sharing scheme PIR-MCORAM (Maffei et al.'17), which does not hide user identities, Metal hides the user identities and is 500x faster (in terms of amortized latency) or 10^5x faster (in terms of worst-case latency).

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Heterogeneous Private Information Retrieval

Hamid Mozaffari (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst)

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Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning

Harsh Chaudhari (Indian Institute of Science, Bangalore), Rahul Rachuri (Aarhus University, Denmark), Ajith Suresh (Indian Institute of Science, Bangalore)

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Are You Going to Answer That? Measuring User Responses...

Imani N. Sherman (University of Florida), Jasmine D. Bowers (University of Florida), Keith McNamara Jr. (University of Florida), Juan E. Gilbert (University of Florida), Jaime Ruiz (University of Florida), Patrick Traynor (University of Florida)

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SVLAN: Secure & Scalable Network Virtualization

Jonghoon Kwon (ETH), Taeho Lee (ETH), Claude Hähni (ETH), Adrian Perrig (ETH)

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