Under the auspices of the Computational Complexity Foundation (CCF)

REPORTS > KEYWORD > PRIVACY:
Reports tagged with privacy:
TR06-114 | 22nd August 2006
Carl Bosley, Yevgeniy Dodis

#### Does Privacy Require True Randomness?

Most cryptographic primitives require randomness (for example, to generate their secret keys). Usually, one assumes that perfect randomness is available, but, conceivably, such primitives might be built under weaker, more realistic assumptions. This is known to be true for many authentication applications, when entropy alone is typically sufficient. In contrast, ... more >>>

TR10-017 | 10th February 2010
Jonathan Ullman, Salil Vadhan

#### PCPs and the Hardness of Generating Synthetic Data

Revisions: 4

Assuming the existence of one-way functions, we show that there is no
polynomial-time, differentially private algorithm $A$ that takes a database
$D\in (\{0,1\}^d)^n$ and outputs a synthetic database'' $\hat{D}$ all of whose two-way
marginals are approximately equal to those of $D$. (A two-way marginal is the fraction
of database rows ... more >>>

TR11-161 | 4th December 2011
Xin Li

#### Design Extractors, Non-Malleable Condensers and Privacy Amplification

We introduce a new combinatorial object, called a \emph{design extractor}, that has both the properties of a design and an extractor. We give efficient constructions of such objects and show that they can be used in several applications.

\begin{enumerate}
\item {Improving the output length of known non-malleable extractors.} Non-malleable extractors ... more >>>

TR11-166 | 4th December 2011
Xin Li

#### Non-Malleable Extractors for Entropy Rate $<1/2$

Revisions: 1

Dodis and Wichs \cite{DW09} introduced the notion of a non-malleable extractor to study the problem of privacy amplification with an active adversary. A non-malleable extractor is a much stronger version of a strong extractor. Given a weakly-random string $x$ and a uniformly random seed $y$ as the inputs, the non-malleable ... more >>>

TR13-015 | 18th January 2013
Iordanis Kerenidis, Mathieu Laurière, David Xiao

#### New lower bounds for privacy in communication protocols

Communication complexity is a central model of computation introduced by Yao in 1979, where
two players, Alice and Bob, receive inputs x and y respectively and want to compute $f(x; y)$ for some fixed
function f with the least amount of communication. Recently people have revisited the question of the ... more >>>

TR14-149 | 10th November 2014
Kai-Min Chung, Xin Li, Xiaodi Wu

#### Multi-Source Randomness Extractors Against Quantum Side Information, and their Applications

We study the problem of constructing multi-source extractors in the quantum setting, which extract almost uniform random bits against quantum side information collected from several initially independent classical random sources. This is a natural generalization of seeded randomness extraction against quantum side information and classical independent source extraction. With new ... more >>>

TR15-075 | 29th April 2015
Eshan Chattopadhyay, Vipul Goyal, Xin Li

#### Non-Malleable Extractors and Codes, with their Many Tampered Extensions

Revisions: 1

Randomness extractors and error correcting codes are fundamental objects in computer science. Recently, there have been several natural generalizations of these objects, in the context and study of tamper resilient cryptography. These are \emph{seeded non-malleable extractors}, introduced by Dodis and Wichs \cite{DW09}; \emph{seedless non-malleable extractors}, introduced by Cheraghchi and Guruswami ... more >>>

TR16-115 | 30th July 2016
Xin Li

#### Improved Non-Malleable Extractors, Non-Malleable Codes and Independent Source Extractors

In this paper we give improved constructions of several central objects in the literature of randomness extraction and tamper-resilient cryptography. Our main results are:

(1) An explicit seeded non-malleable extractor with error $\epsilon$ and seed length $d=O(\log n)+O(\log(1/\epsilon)\log \log (1/\epsilon))$, that supports min-entropy $k=\Omega(d)$ and outputs $\Omega(k)$ bits. Combined with ... more >>>

TR19-098 | 20th July 2019
Jayadev Acharya, Clement Canonne, Yanjun Han, Ziteng Sun, Himanshu Tyagi

#### Domain Compression and its Application to Randomness-Optimal Distributed Goodness-of-Fit

We study goodness-of-fit of discrete distributions in the distributed setting, where samples are divided between multiple users who can only release a limited amount of information about their samples due to various information constraints. Recently, a subset of the authors showed that having access to a common random seed (i.e., ... more >>>

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