2,124 research outputs found
Conclave: secure multi-party computation on big data (extended TR)
Secure Multi-Party Computation (MPC) allows mutually distrusting parties to
run joint computations without revealing private data. Current MPC algorithms
scale poorly with data size, which makes MPC on "big data" prohibitively slow
and inhibits its practical use.
Many relational analytics queries can maintain MPC's end-to-end security
guarantee without using cryptographic MPC techniques for all operations.
Conclave is a query compiler that accelerates such queries by transforming them
into a combination of data-parallel, local cleartext processing and small MPC
steps. When parties trust others with specific subsets of the data, Conclave
applies new hybrid MPC-cleartext protocols to run additional steps outside of
MPC and improve scalability further.
Our Conclave prototype generates code for cleartext processing in Python and
Spark, and for secure MPC using the Sharemind and Obliv-C frameworks. Conclave
scales to data sets between three and six orders of magnitude larger than
state-of-the-art MPC frameworks support on their own. Thanks to its hybrid
protocols, Conclave also substantially outperforms SMCQL, the most similar
existing system.Comment: Extended technical report for EuroSys 2019 pape
Prochlo: Strong Privacy for Analytics in the Crowd
The large-scale monitoring of computer users' software activities has become
commonplace, e.g., for application telemetry, error reporting, or demographic
profiling. This paper describes a principled systems architecture---Encode,
Shuffle, Analyze (ESA)---for performing such monitoring with high utility while
also protecting user privacy. The ESA design, and its Prochlo implementation,
are informed by our practical experiences with an existing, large deployment of
privacy-preserving software monitoring.
(cont.; see the paper
Seeking Anonymity in an Internet Panopticon
Obtaining and maintaining anonymity on the Internet is challenging. The state
of the art in deployed tools, such as Tor, uses onion routing (OR) to relay
encrypted connections on a detour passing through randomly chosen relays
scattered around the Internet. Unfortunately, OR is known to be vulnerable at
least in principle to several classes of attacks for which no solution is known
or believed to be forthcoming soon. Current approaches to anonymity also appear
unable to offer accurate, principled measurement of the level or quality of
anonymity a user might obtain.
Toward this end, we offer a high-level view of the Dissent project, the first
systematic effort to build a practical anonymity system based purely on
foundations that offer measurable and formally provable anonymity properties.
Dissent builds on two key pre-existing primitives - verifiable shuffles and
dining cryptographers - but for the first time shows how to scale such
techniques to offer measurable anonymity guarantees to thousands of
participants. Further, Dissent represents the first anonymity system designed
from the ground up to incorporate some systematic countermeasure for each of
the major classes of known vulnerabilities in existing approaches, including
global traffic analysis, active attacks, and intersection attacks. Finally,
because no anonymity protocol alone can address risks such as software exploits
or accidental self-identification, we introduce WiNon, an experimental
operating system architecture to harden the uses of anonymity tools such as Tor
and Dissent against such attacks.Comment: 8 pages, 10 figure
Secure and Scalable Circuit-based Protocol for Multi-Party Private Set Intersection
We propose a novel protocol for computing a circuit which implements the
multi-party private set intersection functionality (PSI). Circuit-based
approach has advantages over using custom protocols to achieve this task, since
many applications of PSI do not require the computation of the intersection
itself, but rather specific functional computations over the items in the
intersection.
Our protocol represents the pioneering circuit-based multi-party PSI
protocol, which builds upon and optimizes the two-party SCS
\cite{huang2012private} protocol. By using secure computation between two
parties, our protocol sidesteps the complexities associated with multi-party
interactions and demonstrates good scalability.
In order to mitigate the high overhead associated with circuit-based
constructions, we have further enhanced our protocol by utilizing simple
hashing scheme and permutation-based hash functions. These tricks have enabled
us to minimize circuit size by employing bucketing techniques while
simultaneously attaining noteworthy reductions in both computation and
communication expenses
- …