Phileas — reproducible automation for hardware security experiments

[ldbo]

Submitting Author: @ldbo
All current maintainers: @ldbo
Package Name: Phileas
One-Line Description of Package: Phileas — reproducible automation for hardware security experiments
Repository Link: https://github.com/ldbo/phileas
Version submitted: v0.5
EiC: TBD
Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

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Code of Conduct & Commitment to Maintain Package

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Description

• Include a brief paragraph describing what your package does:

Phileas is a Python package that improves the sustainability of hardware security experiments. This domain heavily relies on automated experiments, which rely on laboratory instruments to gather many measurements on the device under test. Phileas has different features that improve the scientific sustainability — including reproducibility, maintainability, reliability and transparency — of this process.

• It uses simple, human-readable configuration files to describe complex experiments. This improves the readability and maintainability of the research process, while facilitating information exchange between researchers.
• It provides composable parameter generation strategies that ease the design of simple as well as complex experiments.
• It provides an abstraction layer for configuring heterogeneous instruments and retrieving their state.

Combined, these features enable automation of data-acquisition experiments, producing more reliable procedures that are easy to replicate, extend, and share.

Scope

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  • Data retrieval
  • Data extraction
  • Data processing/munging
  • Data deposition
  • Data validation and testing
  • Data visualization¹
  • Workflow automation
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  • Scientific software wrappers
  • Database interoperability

Domain Specific

• Geospatial
• Education

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  • Who is the target audience and what are scientific applications of this package?

It targets experimental researchers in the field of hardware cybersecurity, or hardware designers willing to evaluate the security of their circuits. They can use it when acquiring datasets, usually to carry out side-channel or fault injection attacks. It has been built in a generic manner, which could make it relevant to other fields requiring the automated configuration of test and measurement instruments.

• Are there other Python packages that accomplish the same thing? If so, how does yours differ?

Some tools focus on instruments and drivers (ChipWhisperer, ChipSHOUTER, Scaffold, pypdm). Others focus on data processing (lascar, SCALib, SCAred, secbench) or provide GUIs for specific experiments (laserstudio). However, to my knowledge, there is no tool that automates complex data acquisition procedures.

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#256, which was reviewed by @eliotwrobson.

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Footnotes

1. Please fill out a pre-submission inquiry before submitting a data visualization package. ↩

[ldbo]

Two notes about the JOSS submission:

• A Zenodo DOI is reserved, however I have not published the package yet. JOSS states that the repository should be archived after the review process is completed. Can I wait for the review process to be done?
• The JOSS paper is in the /joss-paper/ directory of the joss-paper branch. You can find the PDF in the artifacts of this workflow. joss-paper will be a short-lived branch never merged with master. It follows the JOSS submission requirements, but is it ok for pyOpenSci?

[eliotwrobson]

@ldbo those are both fine! We only really need to worry about the parts of the JOSS process once the review is completed. I'll start looking around for an editor.

[ldbo]

Hi @eliotwrobson, I'm just checking in on the status of the review. Is there any update or anything I can provide to help move this forward? Thank you!

[eliotwrobson]

@ldbo sorry for the delays. We're stretched a little thin right now but searching for an editor for this review. Please let us know if you know anybody who could serve as an editor / reviewer for this package!