3 Search Results for "Knudsen, Lars R."

Document
DOI: 10.4230/LIPIcs.ESA.2024.29
A Euclidean Embedding for Computing Persistent Homology with Gaussian Kernels

Authors: Jean-Daniel Boissonnat and Kunal Dutta

Published in: LIPIcs, Volume 308, 32nd Annual European Symposium on Algorithms (ESA 2024)

Abstract
Computing persistent homology of large datasets using Gaussian kernels is useful in the domains of topological data analysis and machine learning as shown by Phillips, Wang and Zheng [SoCG 2015]. However, unlike in the case of persistent homology computation using the Euclidean distance or the k-distance, using Gaussian kernels involves significantly higher overhead, as all distance computations are in terms of the Gaussian kernel distance which is computationally more expensive. Further, most algorithmic implementations (e.g. Gudhi, Ripser, etc.) are based on Euclidean distances, so the question of finding a Euclidean embedding - preferably low-dimensional - that preserves the persistent homology computed with Gaussian kernels, is quite important. We consider the Gaussian kernel power distance (GKPD) given by Phillips, Wang and Zheng. Given an n-point dataset and a relative error parameter {ε} ∈ (0,1], we show that the persistent homology of the {Čech } filtration of the dataset computed using the GKPD can be approximately preserved using O({ε}^{-2}log n) dimensions, under a high stable rank condition. Our results also extend to the Delaunay filtration and the (simpler) case of the weighted Rips filtrations constructed using the GKPD. Compared to the Euclidean embedding for the Gaussian kernel function in ∼ n dimensions, which uses the Cholesky decomposition of the matrix of the kernel function applied to all pairs of data points, our embedding may also be viewed as dimensionality reduction - reducing the dimensionality from n to ∼ log n dimensions. Our proof utilizes the embedding of Chen and Phillips [ALT 2017], based on the Random Fourier Functions of Rahimi and Recht [NeurIPS 2007], together with two novel ingredients. The first one is a new decomposition of the squared radii of {Čech } simplices computed using the GKPD, in terms of the pairwise GKPDs between the vertices, which we state and prove. The second is a new concentration inequality for sums of cosine functions of Gaussian random vectors, which we call Gaussian cosine chaoses. We believe these are of independent interest and will find other applications in future.
Cite as

Jean-Daniel Boissonnat and Kunal Dutta. A Euclidean Embedding for Computing Persistent Homology with Gaussian Kernels. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 29:1-29:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{boissonnat_et_al:LIPIcs.ESA.2024.29,
  author =	{Boissonnat, Jean-Daniel and Dutta, Kunal},
  title =	{{A Euclidean Embedding for Computing Persistent Homology with Gaussian Kernels}},
  booktitle =	{32nd Annual European Symposium on Algorithms (ESA 2024)},
  pages =	{29:1--29:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-338-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{308},
  editor =	{Chan, Timothy and Fischer, Johannes and Iacono, John and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2024.29},
  URN =		{urn:nbn:de:0030-drops-211009},
  doi =		{10.4230/LIPIcs.ESA.2024.29},
  annote =	{Keywords: Persistent homology, Gaussian kernels, Random Fourier Features, Euclidean embedding}
}
Document
DOI: 10.4230/LIPIcs.ITC.2024.8
Breaking RSA Generically Is Equivalent to Factoring, with Preprocessing

Authors: Dana Dachman-Soled, Julian Loss, and Adam O'Neill

Published in: LIPIcs, Volume 304, 5th Conference on Information-Theoretic Cryptography (ITC 2024)

Abstract
We investigate the relationship between the classical RSA and factoring problems when preprocessing is considered. In such a model, adversaries can use an unbounded amount of precomputation to produce an "advice" string to then use during the online phase, when a problem instance becomes known. Previous work (e.g., [Bernstein, Lange ASIACRYPT '13]) has shown that preprocessing attacks significantly improve the runtime of the best-known factoring algorithms. Due to these improvements, we ask whether the relationship between factoring and RSA fundamentally changes when preprocessing is allowed. Specifically, we investigate whether there is a superpolynomial gap between the runtime of the best attack on RSA with preprocessing and on factoring with preprocessing. Our main result rules this out with respect to algorithms that perform generic computation on the RSA instance x^e od N yet arbitrary computation on the modulus N, namely a careful adaptation of the well-known generic ring model of Aggarwal and Maurer (Eurocrypt 2009) to the preprocessing setting. In particular, in this setting we show the existence of a factoring algorithm with polynomially related parameters, for any setting of RSA parameters. Our main technical contribution is a set of new information-theoretic techniques that allow us to handle or eliminate cases in which the Aggarwal and Maurer result does not yield a factoring algorithm in the standard model with parameters that are polynomially related to those of the RSA algorithm. These techniques include two novel compression arguments, and a variant of the Fiat-Naor/Hellman tables construction that is tailored to the factoring setting.
Cite as

Dana Dachman-Soled, Julian Loss, and Adam O'Neill. Breaking RSA Generically Is Equivalent to Factoring, with Preprocessing. In 5th Conference on Information-Theoretic Cryptography (ITC 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 304, pp. 8:1-8:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{dachmansoled_et_al:LIPIcs.ITC.2024.8,
  author =	{Dachman-Soled, Dana and Loss, Julian and O'Neill, Adam},
  title =	{{Breaking RSA Generically Is Equivalent to Factoring, with Preprocessing}},
  booktitle =	{5th Conference on Information-Theoretic Cryptography (ITC 2024)},
  pages =	{8:1--8:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-333-1},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{304},
  editor =	{Aggarwal, Divesh},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITC.2024.8},
  URN =		{urn:nbn:de:0030-drops-205163},
  doi =		{10.4230/LIPIcs.ITC.2024.8},
  annote =	{Keywords: RSA, factoring, generic ring model, preprocessing}
}
Document
DOI: 10.4230/DagSemProc.09031.7
Grøstl - a SHA-3 candidate

Authors: Praveen Gauravaram, Lars R. Knudsen, Krystian Matusiewicz, Florian Mendel, Christian Rechberger, Martin Schläffer, and Søren S. Thomsen

Published in: Dagstuhl Seminar Proceedings, Volume 9031, Symmetric Cryptography (2009)

Abstract
Grøstl is a SHA-3 candidate proposal. Grøstl is an iterated hash function with a compression function built from two fixed, large, distinct permutations. The design of Grøstl is transparent and based on principles very different from those used in the SHA-family. The two permutations are constructed using the wide trail design strategy, which makes it possible to give strong statements about the resistance of Grøstl against large classes of cryptanalytic attacks. Moreover, if these permutations are assumed to be ideal, there is a proof for the security of the hash function. Grøstl is a byte-oriented SP-network which borrows components from the AES. The S-box used is identical to the one used in the block cipher AES and the diffusion layers are constructed in a similar manner to those of the AES. As a consequence there is a very strong confusion and diffusion in Grøstl. Grøstl is a so-called wide-pipe construction where the size of the internal state is significantly larger than the size of the output. This has the effect that all known, generic attacks on the hash function are made much more difficult. Grøstl has good performance on a wide range of platforms and counter-measures against side-channel attacks are well-understood from similar work on the AES.
Cite as

Praveen Gauravaram, Lars R. Knudsen, Krystian Matusiewicz, Florian Mendel, Christian Rechberger, Martin Schläffer, and Søren S. Thomsen. Grøstl - a SHA-3 candidate. In Symmetric Cryptography. Dagstuhl Seminar Proceedings, Volume 9031, pp. 1-33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{gauravaram_et_al:DagSemProc.09031.7,
  author =	{Gauravaram, Praveen and Knudsen, Lars R. and Matusiewicz, Krystian and Mendel, Florian and Rechberger, Christian and Schl\"{a}ffer, Martin and Thomsen, S{\o}ren S.},
  title =	{{Gr{\o}stl - a SHA-3 candidate}},
  booktitle =	{Symmetric Cryptography},
  pages =	{1--33},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9031},
  editor =	{Helena Handschuh and Stefan Lucks and Bart Preneel and Phillip Rogaway},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09031.7},
  URN =		{urn:nbn:de:0030-drops-19554},
  doi =		{10.4230/DagSemProc.09031.7},
  annote =	{Keywords: SHA-3 proposal, hash function}
}
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