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WAGE: An Authenticated Encryption with a Twist

2020· article· en· W3022241651 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIACR Transactions on Symmetric Cryptology · 2020
Typearticle
Languageen
FieldComputer Science
TopicCryptographic Implementations and Security
Canadian institutionsUniversity of WaterlooUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaNational Institute of Standards and TechnologyUniversity of WaterlooU.S. Department of Commerce
KeywordsAuthenticated encryptionPermutation (music)EncryptionBlock cipherComputer sciencePseudorandom permutationDifferential cryptanalysisPseudorandom number generatorRandom permutationMathematicsArithmeticTheoretical computer scienceAlgorithmBlock (permutation group theory)Computer networkCombinatorics

Abstract

fetched live from OpenAlex

This paper presents WAGE, a new lightweight sponge-based authenticated cipher whose underlying permutation is based on a 37-stage Galois NLFSR over F27. At its core, the round function of the permutation consists of the well-analyzed Welch-Gong permutation (WGP), primitive feedback polynomial, a newly designed 7-bit SB sbox and partial word-wise XORs. The construction of the permutation is carried out such that the design of individual components is highly coupled with cryptanalysis and hardware efficiency. As such, we analyze the security of WAGE against differential, linear, algebraic and meet/miss-in-the-middle attacks. For 128-bit authenticated encryption security, WAGE achieves a throughput of 535 Mbps with hardware area of 2540 GE in ASIC ST Micro 90 nm standard cell library. Additionally, WAGE is designed with a twist where its underlying permutation can be efficiently turned into a pseudorandom bit generator based on the WG transformation (WG-PRBG) whose output bits have theoretically proved randomness properties.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.864
Threshold uncertainty score0.795

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.268
Teacher spread0.236 · 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