Zuocheng Ren

dblp:132/0854 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1Security and privacy · 1Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
2 papers
Cryptographic protocols and secure computation · 100%
Computer architecture, parallel and distributed computing, and storage systems
3 papers
Storage systems · 50% Memory systems · 20% Hardware reliability and fault tolerance · 15%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cryptographic protocols and secure computation › verifiable computation
verifiable outsourced computation
0.212015
Efficient RAM and control flow in verifiable outsourced computation · NDSS 2015
Cryptographic protocols and secure computation
verifiable computation
0.212013
Verifying computations with state · SOSP 2013
Memory systems
random-access memory
0.112015
Efficient RAM and control flow in verifiable outsourced computation · NDSS 2015
Cloud and datacenter computing › computation offloading
outsourced computation
0.012013
Verifying computations with state · SOSP 2013

Methods — techniques the papers use, named apart from their topics

proof-based verifiable computation · 0.3cryptography · 0.3fault tolerance · 0.2
YearPublicationVenuePosition
2015 Efficient RAM and control flow in verifiable outsourced computation
Riad S. Wahby, Srinath Setty, Zuocheng Ren, Andrew J. Blumberg, Michael Walfish
NDSS3
2013 Robustness in the Salus Scalable Block Store
Yang Wang 0009, Manos Kapritsos, Zuocheng Ren, Prince Mahajan, Jeevitha Kirubanandam, Lorenzo Alvisi, Michael Dahlin
NSDI3
2013 Verifying computations with state
abstract
When a client outsources a job to a third party (e.g., the cloud), how can the client check the result, without re-executing the computation? Recent work in proof-based verifiable computation has made significant progress on this problem by incorporating deep results from complexity theory and cryptography into built systems. However, these systems work within a stateless model: they exclude computations that interact with RAM or a disk, or for which the client does not have the full input.
Benjamin Braun, Ariel J. Feldman, Zuocheng Ren, Srinath Setty, Andrew J. Blumberg, Michael Walfish
SOSP3