3 Search Results for "Keller, Marcel"

Document
DOI: 10.4230/LIPIcs.WABI.2024.15
Swiftly Identifying Strongly Unique k-Mers

Authors: Jens Zentgraf and Sven Rahmann

Published in: LIPIcs, Volume 312, 24th International Workshop on Algorithms in Bioinformatics (WABI 2024)

Abstract
Motivation. Short DNA sequences of length k that appear in a single location (e.g., at a single genomic position, in a single species from a larger set of species, etc.) are called unique k-mers. They are useful for placing sequenced DNA fragments at the correct location without computing alignments and without ambiguity. However, they are not necessarily robust: A single basepair change may turn a unique k-mer into a different one that may in fact be present at one or more different locations, which may give confusing or contradictory information when attempting to place a read by its k-mer content. A more robust concept are strongly unique k-mers, i.e., unique k-mers for which no Hamming-distance-1 neighbor with conflicting information exists in all of the considered sequences. Given a set of k-mers, it is therefore of interest to have an efficient method that can distinguish k-mers with a Hamming-distance-1 neighbor in the collection from those that do not. Results. We present engineered algorithms to identify and mark within a set K of (canonical) k-mers all elements that have a Hamming-distance-1 neighbor in the same set. One algorithm is based on recursively running a 4-way comparison on sub-intervals of the sorted set. The other algorithm is based on bucketing and running a pairwise bit-parallel Hamming distance test on small buckets of the sorted set. Both methods consider canonical k-mers (i.e., taking reverse complements into account) and allow for efficient parallelization. The methods have been implemented and applied in practice to sets consisting of several billions of k-mers. An optimized combined approach running with 16 threads on a 16-core workstation, yields wall-clock running times below 20 seconds on the 2.5 billion distinct 31-mers of the human telomere-to-telomere reference genome. Availability. An implementation can be found at https://gitlab.com/rahmannlab/strong-k-mers.
Cite as

Jens Zentgraf and Sven Rahmann. Swiftly Identifying Strongly Unique k-Mers. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 312, pp. 15:1-15:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{zentgraf_et_al:LIPIcs.WABI.2024.15,
  author =	{Zentgraf, Jens and Rahmann, Sven},
  title =	{{Swiftly Identifying Strongly Unique k-Mers}},
  booktitle =	{24th International Workshop on Algorithms in Bioinformatics (WABI 2024)},
  pages =	{15:1--15:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-340-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{312},
  editor =	{Pissis, Solon P. and Sung, Wing-Kin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2024.15},
  URN =		{urn:nbn:de:0030-drops-206593},
  doi =		{10.4230/LIPIcs.WABI.2024.15},
  annote =	{Keywords: k-mer, Hamming distance, strong uniqueness, parallelization, algorithm engineering}
}
Document
DOI: 10.4230/LIPIcs.ITC.2024.10
Secure Multiparty Computation of Symmetric Functions with Polylogarithmic Bottleneck Complexity and Correlated Randomness

Authors: Reo Eriguchi

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

Abstract
Bottleneck complexity is an efficiency measure of secure multiparty computation (MPC) protocols introduced to achieve load-balancing in large-scale networks, which is defined as the maximum communication complexity required by any one player within the protocol execution. Towards the goal of achieving low bottleneck complexity, prior works proposed MPC protocols for computing symmetric functions in the correlated randomness model, where players are given input-independent correlated randomness in advance. However, the previous protocols with polylogarithmic bottleneck complexity in the number n of players require a large amount of correlated randomness that is linear in n, which limits the per-party efficiency as receiving and storing correlated randomness are the bottleneck for efficiency. In this work, we present for the first time MPC protocols for symmetric functions such that bottleneck complexity and the amount of correlated randomness are both polylogarithmic in n, assuming semi-honest adversaries colluding with at most n-o(n) players. Furthermore, one of our protocols is even computationally efficient in that each player performs only polylog(n) arithmetic operations while the computational complexity of the previous protocols is O(n). Technically, our efficiency improvements come from novel protocols based on ramp secret sharing to realize basic functionalities with low bottleneck complexity, which we believe may be of interest beyond their applications to secure computation of symmetric functions.
Cite as

Reo Eriguchi. Secure Multiparty Computation of Symmetric Functions with Polylogarithmic Bottleneck Complexity and Correlated Randomness. In 5th Conference on Information-Theoretic Cryptography (ITC 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 304, pp. 10:1-10:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{eriguchi:LIPIcs.ITC.2024.10,
  author =	{Eriguchi, Reo},
  title =	{{Secure Multiparty Computation of Symmetric Functions with Polylogarithmic Bottleneck Complexity and Correlated Randomness}},
  booktitle =	{5th Conference on Information-Theoretic Cryptography (ITC 2024)},
  pages =	{10:1--10:22},
  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.2024.10},
  URN =		{urn:nbn:de:0030-drops-205182},
  doi =		{10.4230/LIPIcs.ITC.2024.10},
  annote =	{Keywords: Secure multiparty computation, Bottleneck complexity, Secret sharing}
}
Document
DOI: 10.4230/LIPIcs.ITC.2020.5
Use Your Brain! Arithmetic 3PC for Any Modulus with Active Security

Authors: Hendrik Eerikson, Marcel Keller, Claudio Orlandi, Pille Pullonen, Joonas Puura, and Mark Simkin

Published in: LIPIcs, Volume 163, 1st Conference on Information-Theoretic Cryptography (ITC 2020)

Abstract
Secure multiparty computation (MPC) allows a set of mutually distrustful parties to compute a public function on their private inputs without revealing anything beyond the output of the computation. This paper focuses on the specific case of actively secure three-party computation with an honest majority. In particular, we are interested in solutions which allow to evaluate arithmetic circuits over real-world CPU word sizes, like 32- and 64-bit words. Our starting point is the novel compiler of Damgård et al. from CRYPTO 2018. First, we present an improved version of it which reduces the online communication complexity by a factor of 2. Next, we replace their preprocessing protocol (with arithmetic modulo a large prime) with a more efficient preprocessing which only performs arithmetic modulo powers of two. Finally, we present a novel "postprocessing" check which replaces the preprocessing phase. These protocols offer different efficiency tradeoffs and can therefore outperform each other in different deployment settings. We demonstrate this with benchmarks in a LAN and different WAN settings. Concretely, we achieve a throughput of 1 million 64-bit multiplications per second with parties located in different continents and 3 million in one location.
Cite as

Hendrik Eerikson, Marcel Keller, Claudio Orlandi, Pille Pullonen, Joonas Puura, and Mark Simkin. Use Your Brain! Arithmetic 3PC for Any Modulus with Active Security. In 1st Conference on Information-Theoretic Cryptography (ITC 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 163, pp. 5:1-5:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{eerikson_et_al:LIPIcs.ITC.2020.5,
  author =	{Eerikson, Hendrik and Keller, Marcel and Orlandi, Claudio and Pullonen, Pille and Puura, Joonas and Simkin, Mark},
  title =	{{Use Your Brain! Arithmetic 3PC for Any Modulus with Active Security}},
  booktitle =	{1st Conference on Information-Theoretic Cryptography (ITC 2020)},
  pages =	{5:1--5:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-151-1},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{163},
  editor =	{Tauman Kalai, Yael and Smith, Adam D. and Wichs, Daniel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITC.2020.5},
  URN =		{urn:nbn:de:0030-drops-121104},
  doi =		{10.4230/LIPIcs.ITC.2020.5},
  annote =	{Keywords: Secure Multiparty Computation, Information Theoretic Security}
}
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