1,012 research outputs found
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications
We present Chameleon, a novel hybrid (mixed-protocol) framework for secure
function evaluation (SFE) which enables two parties to jointly compute a
function without disclosing their private inputs. Chameleon combines the best
aspects of generic SFE protocols with the ones that are based upon additive
secret sharing. In particular, the framework performs linear operations in the
ring using additively secret shared values and nonlinear
operations using Yao's Garbled Circuits or the Goldreich-Micali-Wigderson
protocol. Chameleon departs from the common assumption of additive or linear
secret sharing models where three or more parties need to communicate in the
online phase: the framework allows two parties with private inputs to
communicate in the online phase under the assumption of a third node generating
correlated randomness in an offline phase. Almost all of the heavy
cryptographic operations are precomputed in an offline phase which
substantially reduces the communication overhead. Chameleon is both scalable
and significantly more efficient than the ABY framework (NDSS'15) it is based
on. Our framework supports signed fixed-point numbers. In particular,
Chameleon's vector dot product of signed fixed-point numbers improves the
efficiency of mining and classification of encrypted data for algorithms based
upon heavy matrix multiplications. Our evaluation of Chameleon on a 5 layer
convolutional deep neural network shows 133x and 4.2x faster executions than
Microsoft CryptoNets (ICML'16) and MiniONN (CCS'17), respectively
Asynchronous Multi-Party Quantum Computation
Multi-party quantum computation (MPQC) allows a set of parties to securely compute a quantum circuit over private quantum data. Current MPQC protocols rely on the fact that the network is synchronous, i.e., messages sent are guaranteed to be delivered within a known fixed delay upper bound, and unfortunately completely break down even when only a single message arrives late.
Motivated by real-world networks, the seminal work of Ben-Or, Canetti and Goldreich (STOC\u2793) initiated the study of multi-party computation for classical circuits over asynchronous networks, where the network delay can be arbitrary. In this work, we begin the study of asynchronous multi-party quantum computation (AMPQC) protocols, where the circuit to compute is quantum.
Our results completely characterize the optimal achievable corruption threshold: we present an n-party AMPQC protocol secure up to t < n/4 corruptions, and an impossibility result when t ? n/4 parties are corrupted. Remarkably, this characterization differs from the analogous classical setting, where the optimal corruption threshold is t < n/3
Computer Science and Game Theory: A Brief Survey
There has been a remarkable increase in work at the interface of computer
science and game theory in the past decade. In this article I survey some of
the main themes of work in the area, with a focus on the work in computer
science. Given the length constraints, I make no attempt at being
comprehensive, especially since other surveys are also available, and a
comprehensive survey book will appear shortly.Comment: To appear; Palgrave Dictionary of Economic
The Crypto-democracy and the Trustworthy
In the current architecture of the Internet, there is a strong asymmetry in
terms of power between the entities that gather and process personal data
(e.g., major Internet companies, telecom operators, cloud providers, ...) and
the individuals from which this personal data is issued. In particular,
individuals have no choice but to blindly trust that these entities will
respect their privacy and protect their personal data. In this position paper,
we address this issue by proposing an utopian crypto-democracy model based on
existing scientific achievements from the field of cryptography. More
precisely, our main objective is to show that cryptographic primitives,
including in particular secure multiparty computation, offer a practical
solution to protect privacy while minimizing the trust assumptions. In the
crypto-democracy envisioned, individuals do not have to trust a single physical
entity with their personal data but rather their data is distributed among
several institutions. Together these institutions form a virtual entity called
the Trustworthy that is responsible for the storage of this data but which can
also compute on it (provided first that all the institutions agree on this).
Finally, we also propose a realistic proof-of-concept of the Trustworthy, in
which the roles of institutions are played by universities. This
proof-of-concept would have an important impact in demonstrating the
possibilities offered by the crypto-democracy paradigm.Comment: DPM 201
Scalable and Secure Aggregation in Distributed Networks
We consider the problem of computing an aggregation function in a
\emph{secure} and \emph{scalable} way. Whereas previous distributed solutions
with similar security guarantees have a communication cost of , we
present a distributed protocol that requires only a communication complexity of
, which we prove is near-optimal. Our protocol ensures perfect
security against a computationally-bounded adversary, tolerates
malicious nodes for any constant (not
depending on ), and outputs the exact value of the aggregated function with
high probability
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