44,061 research outputs found
Non-Malleable Extractors and Codes, with their Many Tampered Extensions
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 seeded non-malleable extractors, introduced in [DW09]; seedless
non-malleable extractors, introduced in [CG14b]; and non-malleable codes,
introduced in [DPW10].
However, explicit constructions of non-malleable extractors appear to be
hard, and the known constructions are far behind their non-tampered
counterparts.
In this paper we make progress towards solving the above problems. Our
contributions are as follows.
(1) We construct an explicit seeded non-malleable extractor for min-entropy
. This dramatically improves all previous results and gives a
simpler 2-round privacy amplification protocol with optimal entropy loss,
matching the best known result in [Li15b].
(2) We construct the first explicit non-malleable two-source extractor for
min-entropy , with output size and
error .
(3) We initiate the study of two natural generalizations of seedless
non-malleable extractors and non-malleable codes, where the sources or the
codeword may be tampered many times. We construct the first explicit
non-malleable two-source extractor with tampering degree up to
, which works for min-entropy , with
output size and error . We show that we can
efficiently sample uniformly from any pre-image. By the connection in [CG14b],
we also obtain the first explicit non-malleable codes with tampering degree
up to , relative rate , and error
.Comment: 50 pages; see paper for full abstrac
Inapproximability of Combinatorial Optimization Problems
We survey results on the hardness of approximating combinatorial optimization
problems
On the Doubly Sparse Compressed Sensing Problem
A new variant of the Compressed Sensing problem is investigated when the
number of measurements corrupted by errors is upper bounded by some value l but
there are no more restrictions on errors. We prove that in this case it is
enough to make 2(t+l) measurements, where t is the sparsity of original data.
Moreover for this case a rather simple recovery algorithm is proposed. An
analog of the Singleton bound from coding theory is derived what proves
optimality of the corresponding measurement matrices.Comment: 6 pages, IMACC2015 (accepted
Deterministic Construction of Binary, Bipolar and Ternary Compressed Sensing Matrices
In this paper we establish the connection between the Orthogonal Optical
Codes (OOC) and binary compressed sensing matrices. We also introduce
deterministic bipolar RIP fulfilling matrices of order
such that . The columns of these matrices are binary BCH code vectors where the
zeros are replaced by -1. Since the RIP is established by means of coherence,
the simple greedy algorithms such as Matching Pursuit are able to recover the
sparse solution from the noiseless samples. Due to the cyclic property of the
BCH codes, we show that the FFT algorithm can be employed in the reconstruction
methods to considerably reduce the computational complexity. In addition, we
combine the binary and bipolar matrices to form ternary sensing matrices
( elements) that satisfy the RIP condition.Comment: The paper is accepted for publication in IEEE Transaction on
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