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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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https://doi.org/10.5281/zenodo...
Dataset . 2021
License: CC BY
Data sources: Sygma
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Magnifying Side-Channel Leakage of Lattice-Based Cryptosystems with Chosen Ciphertexts: The Case Study of Kyber (Dataset)

Authors: Xu, Z.; Pemberton, O; Roy, S.; Oswald, D.;

Magnifying Side-Channel Leakage of Lattice-Based Cryptosystems with Chosen Ciphertexts: The Case Study of Kyber (Dataset)

Abstract

This repository contains data to reproduce results from the paper "Magnifying Side-Channel Leakage of Lattice-Based Cryptosystems with Chosen Ciphertexts: The Case Study of Kyber." Abstract In this paper, we propose EM side-channel attacks with carefully constructed ciphertext on Kyber, a lattice-based key encapsulation mechanism, which is a candidate of NIST Post-Quantum Cryptography standardization project. We demonstrate that specially chosen ciphertexts allow an adversary to modulate the leakage of a target device and enable full key extraction with a small number of traces through simple power analysis. Compared to prior research, our techniques require a lower number of traces and avoid the need for template attacks. We practically evaluate our methods using both a clean reference implementation of Kyber and the ARM-optimized pqm4 library. For the reference implementation, we target the leakage of the output of the inverse NTT computation and recover the full key with only four traces. For the pqm4 implementation, we develop a message-recovery attack that leads to extraction of the full secret-key with between eight and 960 traces (or 184 traces for recovering 98% of the secret-key), depending on the compiler optimization level. We discuss the relevance of our findings to other lattice-based schemes and explore potential countermeasures.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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