708 research outputs found
Extracting the Kolmogorov Complexity of Strings and Sequences from Sources with Limited Independence
An infinite binary sequence has randomness rate at least if, for
almost every , the Kolmogorov complexity of its prefix of length is at
least . It is known that for every rational , on
one hand, there exists sequences with randomness rate that can not be
effectively transformed into a sequence with randomness rate higher than
and, on the other hand, any two independent sequences with randomness
rate can be transformed into a sequence with randomness rate higher
than . We show that the latter result holds even if the two input
sequences have linear dependency (which, informally speaking, means that all
prefixes of length of the two sequences have in common a constant fraction
of their information). The similar problem is studied for finite strings. It is
shown that from any two strings with sufficiently large Kolmogorov complexity
and sufficiently small dependence, one can effectively construct a string that
is random even conditioned by any one of the input strings
Impossibility of independence amplification in Kolmogorov complexity theory
The paper studies randomness extraction from sources with bounded
independence and the issue of independence amplification of sources, using the
framework of Kolmogorov complexity. The dependency of strings and is
, where
denotes the Kolmogorov complexity. It is shown that there exists a
computable Kolmogorov extractor such that, for any two -bit strings with
complexity and dependency , it outputs a string of length
with complexity conditioned by any one of the input
strings. It is proven that the above are the optimal parameters a Kolmogorov
extractor can achieve. It is shown that independence amplification cannot be
effectively realized. Specifically, if (after excluding a trivial case) there
exist computable functions and such that for all -bit strings and with , then
Counting dependent and independent strings
The paper gives estimations for the sizes of the the following sets: (1) the
set of strings that have a given dependency with a fixed string, (2) the set of
strings that are pairwise \alpha independent, (3) the set of strings that are
mutually \alpha independent. The relevant definitions are as follows: C(x) is
the Kolmogorov complexity of the string x. A string y has \alpha -dependency
with a string x if C(y) - C(y|x) \geq \alpha. A set of strings {x_1, \ldots,
x_t} is pairwise \alpha-independent if for all i different from j, C(x_i) -
C(x_i | x_j) \leq \alpha. A tuple of strings (x_1, \ldots, x_t) is mutually
\alpha-independent if C(x_{\pi(1)} \ldots x_{\pi(t)}) \geq C(x_1) + \ldots +
C(x_t) - \alpha, for every permutation \pi of [t]
Influence tests I: ideal composite hypothesis tests, and causal semimeasures
Ratios of universal enumerable semimeasures corresponding to hypotheses are
investigated as a solution for statistical composite hypotheses testing if an
unbounded amount of computation time can be assumed.
Influence testing for discrete time series is defined using generalized
structural equations. Several ideal tests are introduced, and it is argued that
when Halting information is transmitted, in some cases, instantaneous cause and
consequence can be inferred where this is not possible classically.
The approach is contrasted with Bayesian definitions of influence, where it
is left open whether all Bayesian causal associations of universal semimeasures
are equal within a constant. Finally the approach is also contrasted with
existing engineering procedures for influence and theoretical definitions of
causation.Comment: 29 pages, 3 figures, draf
Shannon Information and Kolmogorov Complexity
We compare the elementary theories of Shannon information and Kolmogorov
complexity, the extent to which they have a common purpose, and where they are
fundamentally different. We discuss and relate the basic notions of both
theories: Shannon entropy versus Kolmogorov complexity, the relation of both to
universal coding, Shannon mutual information versus Kolmogorov (`algorithmic')
mutual information, probabilistic sufficient statistic versus algorithmic
sufficient statistic (related to lossy compression in the Shannon theory versus
meaningful information in the Kolmogorov theory), and rate distortion theory
versus Kolmogorov's structure function. Part of the material has appeared in
print before, scattered through various publications, but this is the first
comprehensive systematic comparison. The last mentioned relations are new.Comment: Survey, LaTeX 54 pages, 3 figures, Submitted to IEEE Trans
Information Theor
Deterministic Chaos in Digital Cryptography
This thesis studies the application of deterministic chaos to digital
cryptography. Cryptographic systems such as pseudo-random generators
(PRNG), block ciphers and hash functions are regarded as a dynamic
system (X, j), where X is a state space (Le. message space)
and f : X -+ X is an iterated function. In both chaos theory and
cryptography, the object of study is a dynamic system that performs
an iterative nonlinear transformation of information in an apparently
unpredictable but deterministic manner. In terms of chaos theory, the
sensitivity to the initial conditions together with the mixing property
ensures cryptographic confusion (statistical independence) and diffusion
(uniform propagation of plaintext and key randomness into cihertext).
This synergetic relationship between the properties of chaotic and
cryptographic systems is considered at both the theoretical and practical
levels: The theoretical background upon which this relationship is
based, includes discussions on chaos, ergodicity, complexity, randomness,
unpredictability and entropy.
Two approaches to the finite-state implementation of chaotic systems
(Le. pseudo-chaos) are considered: (i) floating-point approximation of
continuous-state chaos; (ii) binary pseudo-chaos. An overview is given
of chaotic systems underpinning cryptographic algorithms along with
their strengths and weaknesses. Though all conventional cryposystems
are considered binary pseudo-chaos, neither chaos, nor pseudo-chaos are
sufficient to guarantee cryptographic strength and security.
A dynamic system is said to have an analytical solution Xn = (xo)
if any trajectory point Xn can be computed directly from the initial
conditions Xo, without performing n iterations. A chaotic system with an
analytical solution may have a unpredictable multi-valued map Xn+l =
f(xn). Their floating-point approximation is studied in the context of
pseudo-random generators.
A cryptographic software system E-Larm ™ implementing a multistream
pseudo-chaotic generator is described. Several pseudo-chaotic
systems including the logistic map, sine map, tangent- and logarithm feedback
maps, sawteeth and tent maps are evaluated by means of floating point
computations. Two types of partitioning are used to extract
pseudo-random from the floating-point state variable: (i) combining the
last significant bits of the floating-point number (for nonlinear maps);
and (ii) threshold partitioning (for piecewise linear maps). Multi-round
iterations are produced to decrease the bit dependence and increase non-linearity.
Relationships between pseudo-chaotic systems are introduced
to avoid short cycles (each system influences periodically the states of
other systems used in the encryption session).
An evaluation of cryptographic properties of E-Larm is given using
graphical plots such as state distributions, phase-space portraits, spectral
density Fourier transform, approximated entropy (APEN), cycle length
histogram, as well as a variety of statistical tests from the National Institute
of Standards and Technology (NIST) suite. Though E-Larm passes
all tests recommended by NIST, an approach based on the floating-point
approximation of chaos is inefficient in terms of the quality/performance
ratio (compared with existing PRNG algorithms). Also no solution is
known to control short cycles.
In conclusion, the role of chaos theory in cryptography is identified;
disadvantages of floating-point pseudo-chaos are emphasized although
binary pseudo-chaos is considered useful for cryptographic applications.Durand Technology Limite
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