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Dawn Song

Researcher at University of California, Berkeley

Publications -  504
Citations -  75245

Dawn Song is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Computer science & Deep learning. The author has an hindex of 117, co-authored 460 publications receiving 61572 citations. Previous affiliations of Dawn Song include FireEye, Inc. & University of California.

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Proceedings ArticleDOI

Practical techniques for searches on encrypted data

TL;DR: This work describes the cryptographic schemes for the problem of searching on encrypted data and provides proofs of security for the resulting crypto systems, and presents simple, fast, and practical algorithms that are practical to use today.
Proceedings ArticleDOI

Random key predistribution schemes for sensor networks

TL;DR: The random-pairwise keys scheme is presented, which perfectly preserves the secrecy of the rest of the network when any node is captured, and also enables node-to-node authentication and quorum-based revocation.
Proceedings ArticleDOI

Provable data possession at untrusted stores

TL;DR: The provable data possession (PDP) model as discussed by the authors allows a client that has stored data at an untrusted server to verify that the server possesses the original data without retrieving it.
Journal ArticleDOI

Advances and open problems in federated learning

Peter Kairouz, +58 more
TL;DR: In this article, the authors describe the state-of-the-art in the field of federated learning from the perspective of distributed optimization, cryptography, security, differential privacy, fairness, compressed sensing, systems, information theory, and statistics.
Posted Content

Provable Data Possession at Untrusted Stores.

TL;DR: Ateniese et al. as discussed by the authors introduced the provable data possession (PDP) model, which allows a client that has stored data at an untrusted server to verify that the server possesses the original data without retrieving it.