MétaCan
Menu
Back to cohort

SIFA: Exploiting Ineffective Fault Inductions on Symmetric Cryptography

2018· article· en· W4251236654 on OpenAlexaff
Christoph Dobraunig, Maria Eichlseder, Thomas Korak, Stefan Mangard, Florian Mendel, Robert Primas

Bibliographic record

VenueIACR Transactions on Cryptographic Hardware and Embedded Systems · 2018
Typearticle
Languageen
FieldComputer Science
TopicCryptographic Implementations and Security
Canadian institutionsInfineon Technologies (Canada)
FundersBundesministerium für Verkehr, Innovation und TechnologieÖsterreichische ForschungsförderungsgesellschaftBundesministerium für Wissenschaft, Forschung und WirtschaftAustrian Science FundEuropean Commission
KeywordsFault (geology)Computer scienceExploitByteFault modelFault coverageComputer securityStuck-at faultFault indicatorCryptographyFault detection and isolationEngineeringArtificial intelligenceComputer hardwareSeismology

Abstract

fetched live from OpenAlex

Since the seminal work of Boneh et al., the threat of fault attacks has been widely known and techniques for fault attacks and countermeasures have been studied extensively. The vast majority of the literature on fault attacks focuses on the ability of fault attacks to change an intermediate value to a faulty one, such as differential fault analysis (DFA), collision fault analysis, statistical fault attack (SFA), fault sensitivity analysis, or differential fault intensity analysis (DFIA). The other aspect of faults—that faults can be induced and do not change a value—has been researched far less. In case of symmetric ciphers, ineffective fault attacks (IFA) exploit this aspect. However, IFA relies on the ability of an attacker to reliably induce reproducible deterministic faults like stuck-at faults on parts of small values (e.g., one bit or byte), which is often considered to be impracticable.As a consequence, most countermeasures against fault attacks do not focus on such attacks, but on attacks exploiting changes of intermediate values and usually try to detect such a change (detection-based), or to destroy the exploitable information if a fault happens (infective countermeasures). Such countermeasures implicitly assume that the release of “fault-free” ciphertexts in the presence of a fault-inducing attacker does not reveal any exploitable information. In this work, we show that this assumption is not valid and we present novel fault attacks that work in the presence of detection-based and infective countermeasures. The attacks exploit the fact that intermediate values leading to “fault-free” ciphertexts show a non-uniform distribution, while they should be distributed uniformly. The presented attacks are entirely practical and are demonstrated to work for software implementations of AES and for a hardware co-processor. These practical attacks rely on fault induction by means of clock glitches and hence, are achieved using only low-cost equipment. This is feasible because our attack is very robust under noisy fault induction attempts and does not require the attacker to model or profile the exact fault effect. We target two types of countermeasures as examples: simple time redundancy with comparison and several infective countermeasures. However, our attacks can be applied to a wider range of countermeasures and are not restricted to these two countermeasures.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.025
GPT teacher head0.275
Teacher spread0.250 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations153
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueIACR Transactions on Cryptographic Hardware and Embedded SystemsSame topicCryptographic Implementations and SecurityFrench-language works237,207