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Phase Modulation Side Channels: Jittery JTAG for On-Chip Voltage Measurements

2024· article· en· W4402271882 on OpenAlexaff
Colin O’Flynn

Bibliographic record

VenueIACR Transactions on Cryptographic Hardware and Embedded Systems · 2024
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsDalhousie University
Fundersnot available
KeywordsChipMaterials scienceVoltageModulation (music)Phase (matter)OptoelectronicsElectrical engineeringChemistryEngineeringPhysicsAcoustics

Abstract

fetched live from OpenAlex

Measuring fluctuations of the clock phase was identified as a source of leakage in early electromagnetic side-channel investigations. Despite this, only recently was measuring the clock phase (or jitter) of digital signals (not electromagnetic signals) from a target used as a source of exploitable leakage. As the phase of a clock output will be related to signal propagation delay through the target, and this propagation delay is related to voltage, this means that most digital devices perform an unintended phase modulation (PM) of their internal voltage onto clock outputs.This paper first demonstrates an unprofiled CPA attack against a Cortex-M microcontroller using the phase of a clock output, observing the signal on both optically isolated and capacitively isolated paths. The unprofiled attack takes only 2–4x more traces than an attack using a classic shunt-resistor measurement.It is then demonstrated how the JTAG bypass mode can be used to force a clock through a digital device. This forced clock signal can then be used as a highly effective oscilloscope that is located on the target device. As the attack does not require modifications to the device (such as capacitor removal or heat spreader removal) it is difficult to detect using existing countermeasures. The example attack over JTAG uses an unprofiled CPA attack, requiring only about 5x more traces than an ideal shunt-resistor based measurement. In addition, a version of this attack using a fault correlation analysis attack is also demonstrated.Countermeasures are discussed, and a simple resampling countermeasure is tested. All tools both offensive and defensive presented in the paper have been released under open-source licenses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.281
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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