Search arXiv⌕ Search

arXiv · 2610.19852

Global and Local Entropy Tests for STL Files Under IEEE-754 Validity Constraints

Abstract

Shannon entropy is a standard measure of ciphertext randomness, evaluated either globally over the byte histogram of the entire ciphertext or locally as the average over non-overlapping blocks of ?xed size. While the global statistic captures only the overall byte distribution, the local statistic is also sensitive to non-randomness that is con?ned to parts of the ciphertext. Both measures are commonly assessed against reference values derived under the assumption of independent uniform bytes. However, STL encodes most numerical data as single-precision IEEE-754 ?oats, and format validity requires them to be ?nite, causing nonuniform byte probabilities and dependence between the two bytes of each exponent pair. We derive the exact mean and variance of entropy under the valid-STL (VSTL) distribution, which assigns equal probability to every admissible sequence of triangle records, and provide second-order expansions that keep the global reference values practical to compute at large ?le sizes. Using these expansions, we establish a two-sided hypothesis test for the global entropy statistic, whose limiting value is lowered from 8 to 7.99991479609 bits. The format constraints also change the local entropy reference: applying the capacity energy criterion to triangle records selects a block size of 1950 bytes instead of 1936 bytes, with an exact reference mean of 7.903106732975 rather than 7.902469316647 bits. Although small, these shifts are su?cient to place the VSTL reference means outside the conventional 95% acceptance intervals at practical ?le sizes, making unadjusted entropy tests prone to falsely rejecting ideal VSTL ciphertexts. Monte-Carlo simulations con?rm all reference values within sampling error. We therefore recommend using the format-speci?c reference values derived here to evaluate STL ciphers.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tonislav Troev, Borislav Stoyanov. 2026-10-14. Global and Local Entropy Tests for STL Files Under IEEE-754 Validity Constraints. https://arxiv.org/abs/2610.19852

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Direction-Shift Keying for High-Mobility mmWave Communications: Geometry-Based Resilience to Short Channel Coherence Times and Phase Noise

Communication reliability in high-mobility millimeter-wave (mmWave) systems is fundamentally challenged by rapid channel variations, manifested in short channel coherence times, and phase noise, which necessitate frequent channel estimation and phase tracking. To overcome these limitations, we introduce Direction-Shift Keying (DSK), a geometry-based modulation scheme that exploits the relative stability of propagation directions rather than the rapidly varying amplitude and phase of the wireless channel. DSK conveys information through distinguishable directions of arrival (DoAs), enabled by a distributed antenna system (DAS), thereby shifting the communication principle from channel-dependent to geometry-dependent signaling. We first derive the structure of the optimal DSK detector for a mobile device equipped with an arbitrary number of antennas. We then establish the fundamental law governing the temporal stability of propagation directions, termed Direction Coherence Time (DCT), and show that DCT scales as $d/v$, where $d$ is the transmitter--receiver distance and $v$ is the relative velocity. In contrast, conventional Channel Coherence Time (CCT) scales as $λ/v$, where $λ$ denotes the wavelength, revealing a coherence-time advantage on the order of $d/λ$, potentially exceeding four orders of magnitude in mmWave systems. Furthermore, we establish the inherent invariance of DSK to common phase rotations, providing resilience to common oscillator phase noise without explicit phase tracking. Numerical results corroborate the theoretical findings and demonstrate the potential of geometry-based signaling for reliable high-mobility mmWave communications.

cs.IT↗

Conditioning Strengthens Classical Entropy and Matrix Inequalities: A Submodular Approach

Dembo, Cover, and Thomas (1991) developed an elegant information-theoretic framework for proving determinantal inequalities for positive definite matrices, which relies on the structural inequalities of differential entropy. Submodular functions, which subsume entropy, inherently satisfy these structural inequalities because they obey generalized forms of the fundamental properties of entropy -- a chain rule and the property that conditioning reduces the function's value (under an appropriate definition of conditioning). Applying subadditivity, Han's inequality (1978), and partition subadditivity (i.e., subadditivity over a partition) yields Hadamard's, Szász's, and Fischer's inequalities, respectively. Furthermore, this framework recovers Ky Fan's inequality (1955), a strengthening of Hadamard's inequality. We highlight a previously unnoticed information-theoretic insight behind this improvement: conditioning yields a tighter upper bound on the joint entropy than the unconditional one. In this paper, we establish conditional strengthenings of Han's inequality and partition subadditivity in the general setting of submodular functions. We derive equality conditions for these strengthened bounds and characterize when they strictly improve their unconditional counterparts. We specialize these results to differential entropy and apply them to establish strengthened versions of Szász's and Fischer's inequalities. The strengthening of Szász's inequality recovers Ky Fan's inequality as a special case, and is strictly stronger than the classical Szász's inequality for any non-diagonal positive definite matrix. We also derive an inequality concerning eigenvalues, which generalizes and strictly strengthens a corresponding eigenvalue inequality of Ky Fan. We provide numerical examples to explicitly illustrate the tightness of our proposed matrix determinantal bounds.

cs.IT↗

On the Power Distance Representation of Bregman Divergences

We express Bregman divergences between parameters as power distances between corresponding weighted points, and investigate several applications of this representation. First, we show that the Bregman closest pair and diameter problems can be reformulated as bichromatic weighted point problems under the power distance. This reformulation enables Bregman nearest and farthest neighbor queries under power distances to be handled in practice through corresponding Euclidean neighbor queries in one additional dimension, after offsetting the weights. Next, we revisit the problem of computing minimum enclosing Bregman balls (Bregman MEBs) and establish their equivalence to double-sided weight power MEBs. We further show that Bregman MEBs can be approximated by relaxing the double-sided weight power MEB problem to its single-sided weight counterpart. We then present two approaches to solving general power MEB problems: An exact algorithm based on the LP-type framework and an arbitrarily accurate approximation scheme based on iterative Frank-Wolfe optimization. Finally, we show that the potential-function lifting transformations used to construct Bregman Voronoi diagrams can be reinterpreted as classical paraboloid lifting transformations applied to the corresponding weighted point sets. This establishes a direct connection between Bregman Voronoi diagrams and power diagrams, further illustrating how Bregman divergences can be represented as power distances.

cs.IT↗