DROPS

Document

DOI: 10.4230/LIPIcs.SAT.2025.20

Scalable Precise Computation of Shannon Entropy

Authors: Yong Lai, Haolong Tong, Zhenghang Xu, and Minghao Yin

Published in: LIPIcs, Volume 341, 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)

Abstract

Quantitative information flow analyses (QIF) are a class of techniques for measuring the amount of confidential information leaked by a program to its public outputs. Shannon entropy is an important method to quantify the amount of leakage in QIF. This paper focuses on the programs modeled in Boolean constraints and optimizes the two stages of the Shannon entropy computation to implement a scalable precise tool PSE. In the first stage, we design a knowledge compilation language called ADD[∧] that combines Algebraic Decision Diagrams and conjunctive decomposition. ADD[∧] avoids enumerating possible outputs of a program and supports tractable entropy computation. In the second stage, we optimize the model counting queries that are used to compute the probabilities of outputs. We compare PSE with the state-of-the-art probabilistic approximately correct tool EntropyEstimation, which was shown to significantly outperform the previous precise tools. The experimental results demonstrate that PSE solved 56 more benchmarks compared to EntropyEstimation in a total of 459. For 98% of the benchmarks that both PSE and EntropyEstimation solved, PSE is at least 10× as efficient as EntropyEstimation.

Cite as

Yong Lai, Haolong Tong, Zhenghang Xu, and Minghao Yin. Scalable Precise Computation of Shannon Entropy. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 20:1-20:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{lai_et_al:LIPIcs.SAT.2025.20,
  author =	{Lai, Yong and Tong, Haolong and Xu, Zhenghang and Yin, Minghao},
  title =	{{Scalable Precise Computation of Shannon Entropy}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{20:1--20:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-381-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{341},
  editor =	{Berg, Jeremias and Nordstr\"{o}m, Jakob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2025.20},
  URN =		{urn:nbn:de:0030-drops-237540},
  doi =		{10.4230/LIPIcs.SAT.2025.20},
  annote =	{Keywords: Knowledge Compilation, Algebraic Decision Diagrams, Quantitative Information Flow, Shannon Entropy}
}

Search Results

Documents authored by Xu, Zhenghang

Scalable Precise Computation of Shannon Entropy

Abstract

Cite as

Thanks for your feedback!

Could not send message