Dataset Open Access

REASSURE (H2020 731591) ECC Dataset

Lukasz Chmielewski


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  <identifier identifierType="DOI">10.5281/zenodo.3609789</identifier>
  <creators>
    <creator>
      <creatorName>Lukasz Chmielewski</creatorName>
      <affiliation>Riscure</affiliation>
    </creator>
  </creators>
  <titles>
    <title>REASSURE (H2020 731591) ECC Dataset</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2020</publicationYear>
  <subjects>
    <subject>reassure</subject>
    <subject>side-channel attack</subject>
    <subject>ecc</subject>
    <subject>c25519</subject>
    <subject>cryptography</subject>
    <subject>physical security</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2020-01-16</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3609789</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3609788</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/reassure</relatedIdentifier>
  </relatedIdentifiers>
  <version>V1.0</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Datasets collection for ECC (C25519) side-channel traces, as part of REASSURE H2020 731591 project.&lt;/p&gt;

&lt;p&gt;The set &amp;ldquo;REASSURE_c25519_arithm_6k + PatternExtract From 5997 traces + StaticAlign.trs&amp;rdquo; contains electromagnetic traces coming from 5997 executions of Curve25519 $\mu$NaCl Montgomery Ladder scalar multiplication:&lt;br&gt;
&lt;a href="https://eur03.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmunacl.cryptojedi.org%2Fcurve25519-cortexm0.shtml&amp;amp;data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350333478&amp;amp;sdata=m8uJEnfiU%2BAw7s%2Bt%2BKX%2Fgf8RcJM849UH2p2%2B%2FGHJtOs%3D&amp;amp;reserved=0"&gt;http://munacl.cryptojedi.org/curve25519-cortexm0.shtml&lt;/a&gt;&lt;br&gt;
running on the Pi\~{n}ata target:&lt;br&gt;
&lt;a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.riscure.com%2Fproduct%2Fpinata-training-target%2F&amp;amp;data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350333478&amp;amp;sdata=39fNqShJ8l5BoZ4HMtHLgviylORABJyq4Ri1wOQGpOI%3D&amp;amp;reserved=0"&gt;https://www.riscure.com/product/pinata-training-target/&lt;/a&gt;&lt;br&gt;
which is a 32-bit STM32F4 microcontroller with an ARM-based architecture, running at the clock frequency of 168 MHz.&lt;br&gt;
&lt;br&gt;
The implementation employs arithmetic-based conditional swap and is additionally protected with projective coordinate re-randomization and scalar randomization.&lt;br&gt;
Each trace from the dataset represent a single iteration of the Montgomery Ladder scalar multiplication that is cut from the whole execution trace; such trace is labeled with the corresponding cswap condition bit.&lt;br&gt;
Observe that a full scalar can be trivially recovered from the cswap condition bits used in the 255 Montgomery Ladder iterations.&lt;br&gt;
Furthermore, all these cut traces (5997*255=1529235) are aligned to exploit the leakage efficiently.&lt;br&gt;
Details about the implementation and how the traces are aligned are in:&lt;br&gt;
&lt;a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Feprint.iacr.org%2F2016%2F923.pdf&amp;amp;data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350343476&amp;amp;sdata=i3GZpv26FuYFwvOSxGjtXm2EU%2Be5xy5XCHEw%2BkrDuKE%3D&amp;amp;reserved=0"&gt;https://eprint.iacr.org/2016/923.pdf&lt;/a&gt;&lt;br&gt;
&lt;br&gt;
The set &amp;ldquo;REASSURE_c25519_arithm_6k + PatternExtract From 100 traces + StaticAlign.trs&amp;rdquo; contains a part of the 5997 set, but limited to the first 100 full traces.&lt;br&gt;
&lt;br&gt;
The set &amp;ldquo;REASSURE_c25519_arithm_6k_100 full traces.trs&amp;rdquo; contains the full 100 traces (before division).&lt;br&gt;
&lt;br&gt;
Each traces is in the TRS format that is described under the following links:&lt;br&gt;
&lt;a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FRiscure%2Fpython-trsfile&amp;amp;data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350343476&amp;amp;sdata=v78Tofs4%2BWvvSYhtqF7dW2uaU1nanllTXA5RyGshjWU%3D&amp;amp;reserved=0"&gt;https://github.com/Riscure/python-trsfile&lt;/a&gt;&lt;br&gt;
&lt;a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FRiscure%2Fjava-trsfile&amp;amp;data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350353467&amp;amp;sdata=Nw%2FAamSU1RQaoCeIC80786IKn4f%2BuOl7wfyjNk5R1C4%3D&amp;amp;reserved=0"&gt;https://github.com/Riscure/java-trsfile&lt;/a&gt;&lt;br&gt;
&lt;a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FRiscure%2FJlsca&amp;amp;data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350353467&amp;amp;sdata=sVPz0gh96ivEqMNxUNN4C36RV9ulAE%2BOu5DQ0w44Pic%3D&amp;amp;reserved=0"&gt;https://github.com/Riscure/Jlsca&lt;/a&gt;&lt;br&gt;
&lt;br&gt;
Moreover, note that each trs file include a short description inside the file itself.&lt;/p&gt;</description>
    <description descriptionType="Other">Contact: chmielewski@riscure.com</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/731591/">731591</awardNumber>
      <awardTitle>Robust and Efficient Approaches to Evaluating Side Channel and Fault Attack Resilience</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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